Spatiotemporal dissociation of fMRI activity in the caudate nucleus underlies human de novo motor skill learning.

Motor skill learning involves a complex process of generating novel movement patterns guided by evaluative feedback, such as a reward. Previous literature has suggested anteroposteriorly separated circuits in the striatum to be implicated in early goal-directed and later automatic stages of motor skill learning, respectively. However, the involvement of these circuits has not been well elucidated in human de novo motor skill learning, which requires learning arbitrary action-outcome associations and value-based action selection. To investigate this issue, we conducted a human functional MRI (fMRI) experiment in which participants learned to control a computer cursor by manipulating their right fingers. We discovered a double dissociation of fMRI activity in the anterior and posterior caudate nucleus, which was associated with performance in the early and late learning stages. Moreover, cognitive and sensorimotor cortico-caudate interactions predicted individual learning performance. Our results suggest parallel cortico-caudate networks operating in different stages of human de novo motor skill learning.

MRI-visible dilated perivascular spaces in healthy young adults: A twin heritability study.

We investigated the narrow-sense heritability of MRI-visible dilated perivascular spaces (dPVS) in healthy young adult twins and nontwin siblings (138 monozygotic, 79 dizygotic twin pairs, and 133 nontwin sibling pairs; 28.7 ± 3.6 years) from the Human Connectome Project. dPVS volumes within basal ganglia (BGdPVS) and white matter (WMdPVS) were automatically calculated on three-dimensional T2-weighted MRI. In univariate analysis, heritability estimates of BGdPVS and WMdPVS after age and sex adjustment were 65.8% and 90.2%. In bivariate analysis, both BGdPVS and WMdPVS showed low to moderate genetic correlations (.30-.43) but high shared heritabilities (71.8-99.9%) with corresponding regional volumes, intracranial volumes, and other regional dPVS volumes. Older age was significantly associated with larger dPVS volume in both regions even after adjusting for clinical and volumetric variables, while blood pressure was not associated with dPVS volume although there was weak genetic correlation. dPVS volume, particularly WMdPVS, was highly heritable in healthy young adults, adding evidence of a substantial genetic contribution in dPVS development and differential effect by location. Age affects dPVS volume even in young adults, while blood pressure might have limited role in dPVS development in its normal range.

Validation of the Athens Insomnia Scale for screening insomnia in South Korean firefighters and rescue workers.

PURPOSE: Sleep problems are a major cause of occupational stress in firefighters and rescue workers. We evaluated the psychometric properties of the Athens Insomnia Scale (AIS) among South Korean firefighters and rescue workers. METHODS: Structured clinical interviews and self-report questionnaires were administered to 221 firefighters and rescue workers. The Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Index (ISI), Epworth Sleepiness Scale (ESS), Short-Form 36-item Health Survey (SF36), and Alcohol Use Disorder Identification Test-Consumption (AUDIT-C) were used to examine convergent and divergent validity. Test-retest reliability was calculated from a subsample (n = 24). Analysis of internal consistency, factor analysis, and receiver operator characteristic curve analysis were conducted. RESULTS: Cronbach's alpha was 0.88. The mean item-total correlation coefficient was 0.73. The test-retest reliability was excellent (ICC = 0.94). Significant correlations of the AIS with the PSQI, ISI, ESS, and SF36 confirmed convergent validity. Nonsignificant associations of the AIS with the AUDIT-C and socioeconomic status showed divergent validity. Factor analysis revealed a one-factor structure. For groups with different symptom severity, group-specific cutoff scores which may improve positive predictive values were suggested. CONCLUSIONS: The AIS may be a useful tool with good reliability and validity for screening insomnia symptoms in firefighters and rescue workers.

Prediction of Cardiovascular Complication in Patients with Newly Diagnosed Type 2 Diabetes Using an XGBoost/GRU-ODE-Bayes-Based Machine-Learning Algorithm.

BACKGRUOUND: Cardiovascular disease is life-threatening yet preventable for patients with type 2 diabetes mellitus (T2DM). Because each patient with T2DM has a different risk of developing cardiovascular complications, the accurate stratification of cardiovascular risk is critical. In this study, we proposed cardiovascular risk engines based on machine-learning algorithms for newly diagnosed T2DM patients in Korea. METHODS: To develop the machine-learning-based cardiovascular disease engines, we retrospectively analyzed 26,166 newly diagnosed T2DM patients who visited Seoul St. Mary's Hospital between July 2009 and April 2019. To accurately measure diabetes-related cardiovascular events, we designed a buffer (1 year), an observation (1 year), and an outcome period (5 years). The entire dataset was split into training and testing sets in an 8:2 ratio, and this procedure was repeated 100 times. The area under the receiver operating characteristic curve (AUROC) was calculated by 10-fold cross-validation on the training dataset. RESULTS: The machine-learning-based risk engines (AUROC XGBoost=0.781±0.014 and AUROC gated recurrent unit [GRU]-ordinary differential equation [ODE]-Bayes=0.812±0.016) outperformed the conventional regression-based model (AUROC=0.723± 0.036). CONCLUSION: GRU-ODE-Bayes-based cardiovascular risk engine is highly accurate, easily applicable, and can provide valuable information for the individualized treatment of Korean patients with newly diagnosed T2DM.

Improving Machine Learning Diabetes Prediction Models for the Utmost Clinical Effectiveness.

The early prediction of diabetes can facilitate interventions to prevent or delay it. This study proposes a diabetes prediction model based on machine learning (ML) to encourage individuals at risk of diabetes to employ healthy interventions. A total of 38,379 subjects were included. We trained the model on 80% of the subjects and verified its predictive performance on the remaining 20%. Furthermore, the performances of several algorithms were compared, including logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), Cox regression, and XGBoost Survival Embedding (XGBSE). The area under the receiver operating characteristic curve (AUROC) of the XGBoost model was the largest, followed by those of the decision tree, logistic regression, and random forest models. For the survival analysis, XGBSE yielded an AUROC exceeding 0.9 for the 2- to 9-year predictions and a C-index of 0.934, while the Cox regression achieved a C-index of 0.921. After lowering the threshold from 0.5 to 0.25, the sensitivity increased from 0.011 to 0.236 for the 2-year prediction model and from 0.607 to 0.994 for the 9-year prediction model, while the specificity showed negligible changes. We developed a high-performance diabetes prediction model that applied the XGBSE algorithm with threshold adjustment. We plan to use this prediction model in real clinical practice for diabetes prevention after simplifying and validating it externally.

Association Between Airway Parameters and Abdominal Fat Measured via Computed Tomography in Asthmatic Patients.

PURPOSE: We aimed to investigate whether airway parameters, assessed via computed tomography (CT), are associated with abdominal fat areas and to compare the clinical characteristics of asthmatic patients with and without elevated visceral to subcutaneous fat area ratio (EV). METHODS: Asthmatic patients (aged ≥40 years) were prospectively recruited. Chest (airway) and fat areas were assessed via CT. Airway parameters, including bronchial wall thickness (WT), lumen diameter (LD), lumen area (LA), wall area (WA), total area (TA), as well as WA/TA percentage (wall area %) were measured at the apical segmental bronchus in the right upper lobe. Visceral (VFA), subcutaneous (SFA) and total (TFA) fat areas (cm²) were also measured. The correlations between abdominal fat areas and airway parameters were assessed. EV was defined as VFA/SFA ≥ 0.4. RESULTS: Fifty asthmatic patients were included (mean age 62.9 years; 52% female); 38% had severe asthma. Significant correlations were found between VFA and both LD and LA (r = -0.35, P = 0.01; r = -0.34, P = 0.02, respectively), and SFA and both WA and TA (r = 0.38, P = 0.007; r = 0.34, P = 0.02, respectively). Exacerbations, requiring corticosteroid therapy or ER visitation, were significantly more frequent in subjects without EV (83% vs. 34%, P = 0.05). CONCLUSIONS: Abdominal fat is associated with asthma, according to the location of fat accumulation. In asthmatic subjects, visceral fat seems to be attributable to the bronchial luminal narrowing, while subcutaneous fat may be related to thickening of bronchial wall.

Firefighters, posttraumatic stress disorder, and barriers to treatment: Results from a nationwide total population survey.

Repeated exposure to traumatic experiences may put professional firefighters at increased risk of developing posttraumatic stress disorder (PTSD). To date, however, the rate of PTSD symptoms, unmet need for mental health treatment, and barriers to treatment have only been investigated in subsamples rather than the total population of firefighters. We conducted a nationwide, total population-based survey of all currently employed South Korean firefighters (n = 39,562). The overall response rate was 93.8% (n = 37,093), with 68.0% (n = 26,887) complete responses for all variables. The rate of current probable PTSD was estimated as 5.4%. Among those with current probable PTSD (n = 1,995), only a small proportion (9.7%) had received mental health treatment during the past month. For those who had not received treatment, perceived barriers of accessibility to treatment (29.3%) and concerns about potential stigma (33.8%) were reasons for not receiving treatment. Although those with higher PTSD symptom severity and functional impairment were more likely to seek treatment, greater symptom severity and functional impairment were most strongly associated with increased concerns about potential stigma. This nationwide study points to the need for new approaches to promote access to mental health treatment in professional firefighters.

Neurocognitive changes and their neural correlates in patients with type 2 diabetes mellitus.

As the prevalence and life expectancy of type 2 diabetes mellitus (T2DM) continue to increase, the importance of effective detection and intervention for the complications of T2DM, especially neurocognitive complications including cognitive dysfunction and dementia, is receiving greater attention. T2DM is thought to influence cognitive function through an as yet unclear mechanism that involves multiple factors such as hyperglycemia, hypoglycemia, and vascular disease. Recent developments in neuroimaging methods have led to the identification of potential neural correlates of T2DM-related neurocognitive changes, which extend from structural to functional and metabolite alterations in the brain. The evidence indicates various changes in the T2DM brain, including global and regional atrophy, white matter hyperintensity, altered functional connectivity, and changes in neurometabolite levels. Continued neuroimaging research is expected to further elucidate the underpinnings of cognitive decline in T2DM and allow better diagnosis and treatment of the condition.

Disturbance of the glutamatergic system in mood disorders.

The role of glutamatergic system in the neurobiology of mood disorders draws increasing attention, as disturbance of this system is consistently implicated in mood disorders including major depressive disorder and bipolar disorder. Thus, the glutamate hypothesis of mood disorders is expected to complement and improve the prevailing monoamine hypothesis, and may indicate novel therapeutic targets. Since the contribution of astrocytes is found to be crucial not only in the modulation of the glutamatergic system but also in the maintenance of brain energy metabolism, alterations in the astrocytic function and neuroenergetic environment are suggested as the potential neurobiological underpinnings of mood disorders. In the present review, the evidence of glutamatergic abnormalities in mood disorders based on postmortem and magnetic resonance spectroscopy (MRS) studies is presented, and disrupted energy metabolism involving astrocytic dysfunction is proposed as the underlying mechanism linking altered energy metabolism, perturbations in the glutamatergic system, and pathogenesis of mood disorders.

Morphometric changes in lateral ventricles of patients with recent-onset type 2 diabetes mellitus.

It is becoming increasingly evident that type 2 diabetes mellitus can have effects on global and regional brain morphology. Ventricular enlargement reflecting cerebral atrophy has been reported particularly in elderly type 2 diabetes patients. However, little is known about its timing through the disease course and morphological variability. Using the combined volumetric and advanced three-dimensional morphological approach, we identified differences in size and shape of the lateral ventricles between recent-onset type 2 diabetes patients and healthy individuals. High-resolution T1-weighted images were obtained from 23 type 2 diabetes patients whose illness duration was less than 1 year and 23 carefully matched healthy individuals. By volume measurement, we found enlarged lateral and third ventricles in type 2 diabetes patients, relative to healthy individuals (F(1,41 )= 7.96, P = 0.007; F(1,41) = 11.16, P = 0.002, respectively). Morphological analysis revealed that the expansion of lateral ventricles in the diabetic brain was prominent in the bilateral frontal horns. The current findings suggest that atrophic changes particularly of the anterior frontal lobe can occur as early as the first year after the clinical diagnosis of type 2 diabetes mellitus.

Enlarged cavum septum pellucidum as a neurodevelopmental marker in adolescent-onset opiate dependence.

OBJECTIVE: Adolescent-onset exposure to highly addictive substances such as opiates may induce far-reaching deleterious effects on later mental and physical health. However, little is known about the neurodevelopmental basis for adolescent-onset opiate dependence. Here we examined whether having an abnormally large cavum septum pellucidum (CSP), a putative marker of limbic structural maldevelopment, is associated with opiate dependence particularly beginning in adolescence. METHOD: The overall length of the CSP and the prevalence of abnormal enlargement of the CSP were assessed and compared in 65 opiate-dependent subjects (41 adolescent-onset opiate users and 24 adult-onset opiate users) and 67 healthy subjects. RESULTS: Opiate-dependent subjects showed a greater prevalence of abnormal CSP enlargement relative to healthy subjects (odds ratio [OR]=3.64, p=0.034). The overall CSP length of adolescent-onset opiate-dependent subjects was greater, as compared not only with healthy subjects (F1,104=11.03, p=0.001) but also with those who began opiate use during adulthood (F1,61=4.43, p=0.039). CONCLUSIONS: The current findings provide the first evidence that abnormal CSP enlargement, which reflects limbic system dysgenesis of neurodevelopmental origin, may be linked to later development of opiate dependence. In addition, a greater CSP length, which indicates more severe limbic abnormalities, appears to confer higher risk for earlier onset of opiate use.

Network-level structural abnormalities of cerebral cortex in type 1 diabetes mellitus.

Type 1 diabetes mellitus (T1DM) usually begins in childhood and adolescence and causes lifelong damage to several major organs including the brain. Despite increasing evidence of T1DM-induced structural deficits in cortical regions implicated in higher cognitive and emotional functions, little is known whether and how the structural connectivity between these regions is altered in the T1DM brain. Using inter-regional covariance of cortical thickness measurements from high-resolution T1-weighted magnetic resonance data, we examined the topological organizations of cortical structural networks in 81 T1DM patients and 38 healthy subjects. We found a relative absence of hierarchically high-level hubs in the prefrontal lobe of T1DM patients, which suggests ineffective top-down control of the prefrontal cortex in T1DM. Furthermore, inter-network connections between the strategic/executive control system and systems subserving other cortical functions including language and mnemonic/emotional processing were also less integrated in T1DM patients than in healthy individuals. The current results provide structural evidence for T1DM-related dysfunctional cortical organization, which specifically underlie the top-down cognitive control of language, memory, and emotion.