Just do it: A neuropsychological theory of agency, cognition, mood, and dopamine.

Agency is the sense that one has control over one's own actions and the consequences of those actions. Despite the critical role that agency plays in the human condition, little is known about its neural basis. A novel theory proposes that increases in agency disinhibit the dopamine system and thereby increase the number of tonically active dopamine neurons in the ventral tegmental area. The theory, called ADDS (Agency Disinhibits the Dopamine System), proposes a specific neural network that mediates these effects. ADDS accurately predicts a variety of relevant neuroscience results, and makes many novel predictions, including that increases in an agency will (a) increase motivation, (b) improve executive function, (c) facilitate procedural learning, but only in the presence of immediate trial-by-trial feedback, (d) have little or no effect on learning-related effects of stimulus repetition or on standard eyeblink conditioning, (e) facilitate the development of automatic behaviors, but have little or no effect on the production of behaviors that are already automatized, (f) amplify the cognitive benefits of positive mood, and (g) reduce pain. The implications of this new theory are considered for several purely psychological theories that assign prominent roles to agency, including self-efficacy theory, hope theory, and goal-focused positive psychotherapy. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

COVID-19 impacts and inequities among underserved communities with diabetes.

Background: People with diabetes have higher COVID-19 morbidity and mortality. These risks are amplified for underserved communities including racial/ethnic minorities and people with lower socioeconomic status. However, limited research has examined COVID-19 outcomes specifically affecting underserved communities with diabetes. Methods: From November 2021 to July 2022, adults with insulin-requiring diabetes at federally qualified health centers in Florida and California (n = 450) completed surveys examining COVID-19 outcomes and demographics. Surveys assessed COVID-19 severity, vaccination uptake, mask-wearing habits, income changes, and healthcare access changes. Surveys also included the full Coronavirus Anxiety Scale (CAS-19). Descriptive statistics were computed for all outcomes. Between-group comparisons for state and race/ethnicity were evaluated via Chi-Squared, Fisher's Exact, Cochran-Mantel-Haenszel, One-Way ANOVA, and t-tests. Logistic regression determined factors associated with COVID-19 vaccination uptake. Data were self-reported and analyzed cross-sectionally. Results: Overall, 29.7 % reported contracting COVID-19; of those, 45.3 % sought care or were hospitalized. Most (81.3 %) received ≥ 1 vaccine. Hispanics had the highest vaccination rate (91.1 %); Non-Hispanic Blacks (NHBs) had the lowest (73.9 %; p =.0281). Hispanics had 4.63x greater vaccination odds than Non-Hispanic Whites ([NHWs]; 95 % CI = [1.81, 11.89]). NHWs least often wore masks (18.8 %; p <.001). Participants reported pandemic-related healthcare changes (62 %) and higher costs of diabetes medications (41 %). Income loss was more frequent in Florida (76 %; p <.001). NHBs most frequently reported "severe" income loss (26.4 %; p =.0124). Loss of health insurance was more common among NHBs (13.3 %; p =.0416) and in Florida (9.7 %; p =.039). COVID-19 anxiety was highest among NHBs and Hispanics (IQR = [0.0, 3.0]; p =.0232) and in Florida (IQR = [0.0, 2.0]; p =.0435). Conclusions: Underserved communities with diabetes had high COVID-19 vaccine uptake but experienced significant COVID-19-related physical, psychosocial, and financial impacts. NHBs and those in Florida had worse outcomes than other racial/ethnic groups and those in California. Further research, interventions, and policy changes are needed to promote health equity for this population.

Sociodemographic factors associated with major depressive episodes and suicidal ideation among emerging adults with diabetes in the U.S.

Background: Research focused on disparities related to mental health comorbidities, especially among emerging adults with diabetes, is limited. Identifying associated factors of disparities could inform policy decisions to make diabetes-related interdisciplinary care more accessible for vulnerable groups. Method: Using data from the National Survey on Drug Use and Health (2015-2019), we examined disparities in presence of major depressive episode (MDE) and suicidal ideation among emerging adults with diabetes. Survey design-adjusted bivariate and multivariable logistic regression models were used for statistical analyses. Results: The study included 1,125 emerging adults (18-25 years old), with a history of type 1 diabetes (T1D) or type 2 diabetes (T2D). After controlling for sociodemographic and health-related characteristics, we found lower odds of having past-year major MDE for non-Hispanic Black (AOR, 0.42, p=0.032) compared to their non-Hispanic White counterparts. Females were 3.02 times more likely to have past-year MDE than males (AOR, 3.02, p=0.004). The odds of having past-year MDE were 1.96 times higher among individuals who identified as LGB (lesbian, gay, bisexual) (AOR, 1.96, P=0.038). There were no statistically significant disparities in suicidal ideation related to race/ethnicity, sex, education, and family income. However, individuals who identified as LGB had significantly higher likelihood of suicidal ideation than their heterosexual counterparts (AOR, 2.47, P=0.004). Conclusion: Significant disparities related to MDE and suicidal ideation exist based on race/ethnicity, gender, and sexual orientation. Integration of a mental health professional into the multidisciplinary diabetes care team is critical for effective management of comorbid mental health conditions in younger patients with diabetes.

Recruiting historically under-represented individuals into Project ECHO Diabetes: using barrier analysis to understand disparities in clinical research in the USA.

OBJECTIVES: Individuals under-recruited in diabetes research studies include those not seen at endocrinology centres and those from rural, low socioeconomic and/or under-represented racial/ethnic groups. The purpose of this descriptive analysis is to detail recruitment and retention efforts of Project ECHO Diabetes clinical sites affiliated with Stanford University and University of Florida. DESIGN: Prospective collection of participant engagement and qualitative analysis of barriers and facilitators of research engagement within Project ECHO Diabetes, a virtual tele-education programme for healthcare providers in the management of individuals with insulin-requiring diabetes. SETTING: Data were collected at the patient level, provider level and clinic level between 1 May 2021 and 31 July 2022. PARTICIPANTS: Participants and study personnel were recruited from 33 Project ECHO Diabetes sites in California and Florida. OUTCOMES: We report study completion rates for participants recruited into 33 Project ECHO Diabetes sites. Using barrier analysis, a methodology designed for the real-time assessment of interventions and system processes to identify barriers and facilitators, study personnel identified significant barriers to recruitment and retention and mapped them to actionable solutions. RESULTS: In total, 872 participants (California n=495, Florida n=377) were recruited with differing recruitment rates by site (California=52.7%, Florida=21.5%). Barrier analysis identified lack of trust, unreliable contact information, communication issues and institutional review board (IRB) requirements as key recruitment barriers. Culturally congruent staff, community health centre (CHC) support, adequate funding and consent process flexibility were solutions to address recruitment challenges. Barriers to retention were inconsistent postal access, haemoglobin A1c kit collection challenges, COVID-19 pandemic and broadband/connectivity issues. Additional funding supporting research staff and analogue communication methods were identified as solutions address barriers to retention. CONCLUSIONS: Funded partnerships with CHCs, trusted by their local communities, were key in our recruitment and retention strategies. IRB consent process flexibility reduced barriers to recruitment. Recruiting historically under-represented populations is feasible with funding aimed to address structural barriers to research participation.

The Promising Success of Project Extension for Community Healthcare Outcomes (ECHO) Diabetes: Case Series.

BACKGROUND: In the United States, there are over 37 million people with diabetes but only 8000 endocrinologists. Therefore, many people with diabetes receive care exclusively from primary care providers (PCPs). To democratize knowledge regarding insulin-requiring diabetes through tele-education, Stanford University and the University of Florida developed Project Extension for Community Healthcare Outcomes (ECHO) Diabetes. OBJECTIVE: ECHO Diabetes uses a Hub and Spoke model connecting specialists (the "Hub") with PCPs (the "Spokes"). One-hour, weekly sessions include Hub diabetes didactic presentations and Spoke deidentified case presentations. Lessons learned during these sessions target provider knowledge and confidence surrounding diabetes management and patient care. METHODS: Spokes were asked to provide short descriptions of people with diabetes whose diabetes management improved directly or indirectly from their providers' participation or their involvement with a Diabetes Support Coach (DSC). We provide a case series to describe individuals and outcomes. Because this study was not a randomized controlled trial and was a prospective observation of patients with the intervention delivered to providers, the trial is not registered in a public trials registry. RESULTS: A case series of 11 people with diabetes was compiled from 10 PCPs and 1 DSC from California and Florida between 2021 and 2022. The principal impact of ECHO Diabetes is the education amplified from PCPs and DSCs to people with diabetes. In all cases, people with diabetes reported increased engagement and improved diabetes management. Several cases reflected increased access to diabetes technology, improvement in glycemic outcomes, and positive trends in mental health measures. CONCLUSIONS: This case series elucidates the potential value of the ECHO Diabetes program to people with diabetes who receive their diabetes care from PCPs. Those matched with a DSC saw clinically significant improvements in hemoglobin A1c and mental health outcomes.

Interventions to address global inequity in diabetes: international progress.

Diabetes is a serious chronic disease with high associated burden and disproportionate costs to communities based on socioeconomic, gender, racial, and ethnic status. Addressing the complex challenges of global inequity in diabetes will require intentional efforts to focus on broader social contexts and systems that supersede individual-level interventions. We codify and highlight best practice approaches to achieve equity in diabetes care and outcomes on a global scale. We outline action plans to target diabetes equity on the basis of the recommendations established by The Lancet Commission on Diabetes, organising interventions by their effect on changing the ecosystem, building capacity, or improving the clinical practice environment. We present international examples of how to address diabetes inequity in the real world to show that approaches addressing the individual within a larger social context, in addition to addressing structural inequity, hold the greatest promise for creating sustainable and equitable change that curbs the global diabetes crisis.

Blue Circle Health: A Novel Patient-Centered Model of Health Care Delivery for Low-Income Patients With Type 1 Diabetes.

Analog insulins, insulin pumps, and continuous glucose monitors (CGM) have revolutionized type 1 diabetes (T1D) treatment over the last 50 years. Nevertheless, less than 20% of patients in the United States reach guideline-based HbA1c targets. The dysfunctional delivery of U.S. health care has further worsened glycemic outcomes among structurally disadvantaged groups such as non-Hispanic Black and low-income populations. Administrative complexities resulting from mixed insurance coverage and delivery systems, incongruity between effective policies and reimbursement, structural racism, and implicit biases have led to high diabetes care-related costs, provider scarcity and burnout, and patient diabetes distress. The Extension for Community Healthcare Outcomes (ECHO) Diabetes tele-education outreach model was created to increase self-efficacy among primary care providers through a combination of weekly didactic sessions led by a team of diabetes experts and access to community-based peer coaches. As an evolution of ECHO Diabetes, Blue Circle Health has been established as a philanthropically funded health care delivery system, using a whole-person, individualized approach to T1D care for adults living in underserved communities. The program will provide direct-to-patient telehealth services, including diabetes education, management, and related psychological care regardless of ability to pay. Community-based diabetes support coaches will serve as the primary point of contact, or guide on the "Blue Circle Health Member Journey." Access to needed insulins, supplies, and CGMs will be provided at no cost to the individual. Through a continuous learning and improvement model, a person-centered, equitable, accessible, and effective health care delivery model will be built for people living with T1D.

Project ECHO Diabetes Cost Modeling to Support the Replication and Expansion of Tele-mentoring Programs in Non-research Settings.

INTRODUCTION: Project ECHO Diabetes is a tele-education learning model for primary care providers (PCPs) seeking to improve care for patients with diabetes from marginalized communities. Project ECHO Diabetes utilized expert "hub" teams comprising endocrinologists, dieticians, nurses, psychologists, and social workers and "spokes" consisting of PCPs and their patients with diabetes. This Project ECHO Diabetes model provided diabetes support coaches to provide additional support to patients. We sought to estimate the costs of operating a Project ECHO Diabetes hub, inclusive of diabetes support coach costs. METHODS: Data from Project ECHO Diabetes from June 2021 to June 2022 and wages from national databases were used to estimate hub and diabetes support coach costs to operate a 6-month, 24-session Project ECHO Diabetes program at hubs (University of Florida and Stanford University) and spokes (PCP clinic sites in Florida and California). RESULTS: Hub costs for delivering a 6-month Project ECHO Diabetes program to five spoke clinics were $96,873. Personnel costs were the principal driver. Mean cost was $19,673 per spoke clinic and $11.37 per spoke clinic patient. Diabetes support coach costs were estimated per spoke clinic and considered scalable in that they would increase proportionately with the number of spoke clinics in a Project ECHO Diabetes cohort. Mean diabetes support coach costs were $6,506 per spoke clinic and $3.72 per patient. Total program costs per hub were $129,404. Mean cost per clinic was $25,881. Mean cost per patient was $15.03. CONCLUSION: Herein, we document real-world costs to operate a Project ECHO Diabetes hub and diabetes support coaches. Future analysis of Project ECHO Diabetes will include estimates of spoke participation costs and changes in health care costs and savings. As state agencies, insurers, and philanthropies consider the replication of Project ECHO Diabetes, this analysis provides important initial information regarding primary operating costs.

Psychological Outcomes of the COVID-19 Pandemic on People with Type 1 Diabetes Globally: A Scoping Review.

BACKGROUND: People with type 1 diabetes (T1D) face heightened risks for morbidity and mortality from the 2019 Coronavirus (COVID-19). They also have elevated risks for disparate psychological outcomes during the COVID-19 pandemic, given their predisposition to mental health disorders, including anxiety and depression, and skyrocketing rates of these conditions among the general population. METHODS: To investigate the psychological ramifications of the COVID-19 pandemic on people with T1D globally, we conducted a scoping review of recent literature across eight online databases. Articles were screened via a rigorous process, and data pertaining to psychological outcomes were coded into thematic areas for analysis. RESULTS: Forty articles presenting data from 27 countries and 14 categories of psychological outcomes affecting people with T1D were included in this review. Psychological outcomes, in order of most to least frequently identified, included: stress, anxiety, social factors, worry, distress, fear, sleep habits, quality of life, depression, attitudes regarding COVID-19, other psychological issues, mental health services utilization, burnout, and temperament. Recurring findings demonstrated significant increases in the prevalence of mental health conditions, changes in sleeping habits, reductions of social support, and extensive psychosocial concerns among people with T1D. Associations between patients' psychological issues and demographic characteristics, diabetes self-management behaviors, glycemic control, and overall wellbeing were evident. CONCLUSION: During the COVID-19 pandemic, people with T1D experienced pervasive psychological burdens. This review calls for further research examining the long-term impacts of the pandemic and strengthens awareness of the need for interventions to offset psychological challenges affecting people with T1D.

Using Peer Power to Reduce Health Disparities: Implementation of a Diabetes Support Coach Program in Federally Qualified Health Centers.

Community health workers (CHWs) provide vital support to underserved communities in the promotion of health equity by addressing barriers related to the social determinants of health that often prevent people living with diabetes from achieving optimal health outcomes. Peer support programs in diabetes can also offer people living with diabetes invaluable support through a shared understanding of the disease and by offsetting diabetes-related stigma. As part of a Project Extension for Community Healthcare Outcomes (ECHO) Diabetes program, participating federally qualified healthcare centers were provided diabetes support coaches (DSCs) to facilitate patient engagement. DSCs hold invaluable expert knowledge, as they live with diabetes themselves and reside in areas they serve, thus combining the CHW role with peer support models. The use of DSCs and CHWs during the coronavirus disease 2019 pandemic and beyond is highly effective at reaching underserved communities with diabetes and promoting health equity.

On what it means to automatize a rule.

The results of two experiments are reported that included a combined total of approximately 633,000 categorization trials. The experiments investigated the nature of what is automatized after lengthy practice with a rule-guided behavior. The results of both experiments suggest that an abstract rule, if interpreted as a verbal-based strategy, was not automatized during training, but rather the automatization linked a set of stimuli with similar values on one visual dimension to a common motor response. The experiments were designed to test and refine a recent neurocomputational model of how rule-guided behaviors become automatic (Kovacs, Hélie, Tran, & Ashby, 2021). The model assumes that rule-guided behaviors are initially controlled by a distributed neural network centered on rule units in prefrontal cortex, and that in addition to initiating behavior, this network also trains a faster and more direct network that includes projections from visual cortex directly to the rule-sensitive neurons in premotor cortex. The present results support this model and suggest that the projections from visual cortex to prefrontal and premotor cortex are restricted to visual representations of the relevant stimulus dimension only.

A general recognition theory model for identifying an ideal stimulus.

A probabilistic, multidimensional model is described that accounts for sensory and hedonic ratings that are collected from the same experiment. The model combines a general recognition theory model of the sensory ratings with Coombs' unfolding model of the hedonic ratings. The model uses sensory ratings to build a probabilistic, multidimensional representation of the sensory experiences elicited by exposure to each stimulus, and it also builds a similar representation of the hypothetical ideal stimulus in this same space. It accounts for hedonic ratings by measuring differences between the presented stimulus and the imagined ideal on each rated sensory dimension. Therefore, it provides precise estimates of the sensory qualities of the ideal on all rated sensory dimensions. The model is tested successfully against data from a new experiment.

Linear separability, irrelevant variability, and categorization difficulty.

In rule-based (RB) category-learning tasks, the optimal strategy is a simple explicit rule, whereas in information-integration (II) tasks, the optimal strategy is impossible to describe verbally. This study investigates the effects of two different category properties on learning difficulty in category learning tasks-namely, linear separability and variability on stimulus dimensions that are irrelevant to the categorization decision. Previous research had reported that linearly separable II categories are easier to learn than nonlinearly separable categories, but Experiment 1, which compared performance on linearly and nonlinearly separable categories that were equated as closely as possible on all other factors that might affect difficulty, found that linear separability had no effect on learning. Experiments 1 and 2 together also established a novel dissociation between RB and II category learning: increasing variability on irrelevant stimulus dimensions impaired II learning but not RB learning. These results are all predicted by the best available measures of difficulty in RB and II tasks. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Tele-education model for primary care providers to advance diabetes equity: Findings from Project ECHO Diabetes.

Introduction: In the US, many individuals with diabetes do not have consistent access to endocrinologists and therefore rely on primary care providers (PCPs) for their diabetes management. Project ECHO (Extension for Community Healthcare Outcomes) Diabetes, a tele-education model, was developed to empower PCPs to independently manage diabetes, including education on diabetes technology initiation and use, to bridge disparities in diabetes. Methods: PCPs (n=116) who participated in Project ECHO Diabetes and completed pre- and post-intervention surveys were included in this analysis. The survey was administered in California and Florida to participating PCPs via REDCap and paper surveys. This survey aimed to evaluate practice demographics, protocols with adult and pediatric T1D management, challenges, resources, and provider knowledge and confidence in diabetes management. Differences and statistical significance in pre- and post-intervention responses were evaluated via McNemar's tests. Results: PCPs reported improvement in all domains of diabetes education and management. From baseline, PCPs reported improvement in their confidence to serve as the T1D provider for their community (pre vs post: 43.8% vs 68.8%, p=0.005), manage insulin therapy (pre vs post: 62.8% vs 84.3%, p=0.002), and identify symptoms of diabetes distress (pre vs post: 62.8% vs 84.3%, p=0.002) post-intervention. Compared to pre-intervention, providers reported significant improvement in their confidence in all aspects of diabetes technology including prescribing technology (41.2% vs 68.6%, p=0.001), managing insulin pumps (41.2% vs 68.6%, p=0.001) and hybrid closed loop (10.2% vs 26.5%, p=0.033), and interpreting sensor data (41.2% vs 68.6%, p=0.001) post-intervention. Discussion: PCPs who participated in Project ECHO Diabetes reported increased confidence in diabetes management, with notable improvement in their ability to prescribe, manage, and troubleshoot diabetes technology. These data support the use of tele-education of PCPs to increase confidence in diabetes technology management as a feasible strategy to advance equity in diabetes management and outcomes.

When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning.

Providing verbal or written instructions on how to perform optimally in a task is one of the most common ways to teach beginners. This practice is so widely accepted that scholarship primarily focuses on how to provide instructions, not whether these instructions help or not. Here we investigate the benefits of prior instruction on rule-based (RB) category-learning, in which the optimal strategy is a simple explicit rule, and information-integration (II) category-learning, in which the optimal strategy is similarity-based. Participants (N = 58) learned either RB or II categories, with or without verbal and written instruction about the optimal categorization strategy. Instructions significantly improved performance with RB categories but had no effect with II categories. The theoretical and practical implication of these results is discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Democratizing type 1 diabetes specialty care in the primary care setting to reduce health disparities: project extension for community healthcare outcomes (ECHO) T1D.

INTRODUCTION: Project ECHO (Extension for Community Healthcare Outcomes) is a tele-education outreach model that seeks to democratize specialty knowledge to reduce disparities and improve health outcomes. Limited utilization of endocrinologists forces many primary care providers (PCPs) to care for patients with type 1 diabetes (T1D) without specialty support. Accordingly, an ECHO T1D program was developed and piloted in Florida and California. Our goal was to demonstrate the feasibility of an ECHO program focused on T1D and improve PCPs' abilities to manage patients with T1D. RESEARCH DESIGN AND METHODS: Health centers (ie, spokes) were recruited into the ECHO T1D pilot through an innovative approach, focusing on Federally Qualified Health Centers and through identification of high-need catchment areas using the Neighborhood Deprivation Index and provider geocoding. Participating spokes received weekly tele-education provided by the University of Florida and Stanford University hub specialty team through virtual ECHO clinics, real-time support with complex T1D medical decision-making, access to a diabetes support coach, and access to an online repository of diabetes care resources. Participating PCPs completed pre/post-tests assessing diabetes knowledge and confidence and an exit survey gleaning feedback about overall ECHO T1D program experiences. RESULTS: In Florida, 12 spoke sites enrolled with 67 clinics serving >1000 patients with T1D. In California, 11 spoke sites enrolled with 37 clinics serving >900 patients with T1D. During the 6-month intervention, 27 tele-education clinics were offered and n=70 PCPs (22 from Florida, 48 from California) from participating spoke sites completed pre/post-test surveys assessing diabetes care knowledge and confidence in diabetes care. There was statistically significant improvement in diabetes knowledge (p≤0.01) as well as in diabetes confidence (p≤0.01). CONCLUSIONS: The ECHO T1D pilot demonstrated proof of concept for a T1D-specific ECHO program and represents a viable model to reach medically underserved communities which do not use specialists.

Modulation of Dopamine for Adaptive Learning: A Neurocomputational Model.

There have been many proposals that learning rates in the brain are adaptive, in the sense that they increase or decrease depending on environmental conditions. The majority of these models are abstract and make no attempt to describe the neural circuitry that implements the proposed computations. This article describes a biologically detailed computational model that overcomes this shortcoming. Specifically, we propose a neural circuit that implements adaptive learning rates by modulating the gain on the dopamine response to reward prediction errors, and we model activity within this circuit at the level of spiking neurons. The model generates a dopamine signal that depends on the size of the tonically active dopamine neuron population and the phasic spike rate. The model was tested successfully against results from two single-neuron recording studies and a fast-scan cyclic voltammetry study. We conclude by discussing the general applicability of the model to dopamine mediated tasks that transcend the experimental phenomena it was initially designed to address.

Barriers to Technology Use and Endocrinology Care for Underserved Communities With Type 1 Diabetes.

OBJECTIVE: Disparities in type 1 diabetes related to use of technologies like continuous glucose monitors (CGMs) and utilization of diabetes care are pronounced based on socioeconomic status (SES), race, and ethnicity. However, systematic reports of perspectives from patients in vulnerable communities regarding barriers are limited. RESEARCH DESIGN AND METHODS: To better understand barriers, focus groups were conducted in Florida and California with adults ≥18 years old with type 1 diabetes with selection criteria including hospitalization for diabetic ketoacidosis, HbA1c >9%, and/or receiving care at a Federally Qualified Health Center. Sixteen focus groups were conducted in English or Spanish with 86 adults (mean age 42 ± 16.2 years). Transcript themes and pre-focus group demographic survey data were analyzed. In order of frequency, barriers to diabetes technology and endocrinology care included 1) provider level (negative provider encounters), 2) system level (financial coverage), and 3) individual level (preferences). RESULTS: Over 50% of participants had not seen an endocrinologist in the past year or were only seen once including during hospital visits. In Florida, there was less technology use overall (38% used CGMs in FL and 63% in CA; 43% used pumps in FL and 69% in CA) and significant differences in pump use by SES (P = 0.02 in FL; P = 0.08 in CA) and race/ethnicity (P = 0.01 in FL; P = 0.80 in CA). In California, there were significant differences in CGM use by race/ethnicity (P = 0.05 in CA; P = 0.56 in FL) and education level (P = 0.02 in CA; P = 0.90 in FL). CONCLUSIONS: These findings provide novel insights into the experiences of vulnerable communities and demonstrate the need for multilevel interventions aimed at offsetting disparities in diabetes.

A neurocomputational theory of how rule-guided behaviors become automatic.

This article introduces a biologically detailed computational model of how rule-guided behaviors become automatic. The model assumes that initially, rule-guided behaviors are controlled by a distributed neural network centered in the prefrontal cortex, and that in addition to initiating behavior, this network also trains a faster and more direct network that includes projections from sensory association cortex directly to rule-sensitive neurons in the premotor cortex. After much practice, the direct network is sufficient to control the behavior, without prefrontal involvement. The model is implemented as a biologically detailed neural network constructed from spiking neurons and displaying a biologically plausible form of Hebbian learning. The model successfully accounts for single-unit recordings and human behavioral data that are problematic for other models of automaticity. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A role for the medial temporal lobes in category learning.

Despite much research, the role of the medial temporal lobes (MTL) in category learning is unclear. Two unstructured categorization experiments explored conditions that might recruit MTL category learning and memory systems-namely, whether the stimulus display includes one or two stimuli, and whether category membership depends on configural properties of the stimulus features. The results supported three conclusions. First, in agreement with prior research, learning with single stimulus displays depended on striatal-mediated procedural learning. Second, and most important, learning with pair displays was mediated by MTL declarative memory systems. Third, the use of stimuli in which category membership depends on configural properties of the stimulus features made MTL learning slightly more likely. Overall, the results suggested that the MTL are most likely to mediate learning when the participant must decide which of two configural stimuli belongs to a selected category.