Individualized prediction of anxiety and depressive symptoms using gray matter volume in a non-clinical population.

Machine learning is an emerging tool in clinical psychology and neuroscience for the individualized prediction of psychiatric symptoms. However, its application in non-clinical populations is still in its infancy. Given the widespread morphological changes observed in psychiatric disorders, our study applies five supervised machine learning regression algorithms-ridge regression, support vector regression, partial least squares regression, least absolute shrinkage and selection operator regression, and Elastic-Net regression-to predict anxiety and depressive symptom scores. We base these predictions on the whole-brain gray matter volume in a large non-clinical sample (n = 425). Our results demonstrate that machine learning algorithms can effectively predict individual variability in anxiety and depressive symptoms, as measured by the Mood and Anxiety Symptoms Questionnaire. The most discriminative features contributing to the prediction models were primarily located in the prefrontal-parietal, temporal, visual, and sub-cortical regions (e.g. amygdala, hippocampus, and putamen). These regions showed distinct patterns for anxious arousal and high positive affect in three of the five models (partial least squares regression, support vector regression, and ridge regression). Importantly, these predictions were consistent across genders and robust to demographic variability (e.g. age, parental education, etc.). Our findings offer critical insights into the distinct brain morphological patterns underlying specific components of anxiety and depressive symptoms, supporting the existing tripartite theory from a neuroimaging perspective.

The computational and neural substrates of individual differences in impulsivity under loss framework.

Numerous neuroimaging studies have identified significant individual variability in intertemporal choice, often attributed to three neural mechanisms: (1) increased reward circuit activity, (2) decreased cognitive control, and (3) prospection ability. These mechanisms that explain impulsivity, however, have been primarily studied in the gain domain. This study extends this investigation to the loss domain. We employed a hierarchical Bayesian drift-diffusion model (DDM) and the inter-subject representational similarity approach (IS-RSA) to investigate the potential computational neural substrates underlying impulsivity in loss domain across two experiments (n = 155). These experiments utilized a revised intertemporal task that independently manipulated the amounts of immediate and delayed-loss options. Behavioral results demonstrated positive correlations between the drift rate, measured by the DDM, and the impulsivity index K in Exp. 1 (n = 97) and were replicated in Exp. 2 (n = 58). Imaging analyses further revealed that the drift rate significantly mediated the relations between brain properties (e.g., prefrontal cortex activations and gray matter volume in the orbitofrontal cortex and precuneus) and K in Exp. 1. IS-RSA analyses indicated that variability in the drift rate also mediated the associations between inter-subject variations in activation patterns and individual differences in K. These findings suggest that individuals with similar impulsivity levels are likely to exhibit similar value processing patterns, providing a potential explanation for individual differences in impulsivity within a loss framework.

Neurobiological substrates of the dread of future losses.

When anticipating future losses, people respond by exhibiting 1 of 2 starkly distinct behavioral decision patterns: the dread of future losses (DFL) and the preference of future losses (vs. immediate losses). Yet, how to accurately discriminate between those who exhibit dread vs. preference and uncover the potential neurobiological substrates underlying these 2 groups remain understudied. To address this, we designed a novel experimental task in which the DFL group was defined as selecting immediate-loss options >50% in the trials with approximate subjective value in immediate and delayed options (n = 16), otherwise coding as the preference of future losses (PFL). At the behavioral level, DFL exhibited higher weight for delayed losses than immediate losses via the logistic regression model. At the neural level, DFL manifested hypoactivations on subjective valuations of delayed losses, atypical brain pattern when choosing immediate-loss options, and decreased functional coupling between the valuation and choice-systems when making decisions related to immediate-loss alternatives compared with PFL. Moreover, both these brain activations subserving distinct decision processes and their interactions predicted individual decisions and behavioral preferences. Furthermore, morphological analysis also revealed decreased right precuneus volume in DFL compared with PFL, and brain activations related to valuation and choice process mediated the associations between this region volume and behavioral performances. Taken together, these findings help to clarify potential cognitive and neural mechanisms underlying the DFL and provide a clear discrimination strategy.

Distributed attribute representation in the superior parietal lobe during probabilistic decision-making.

Several studies have examined the neural substrates of probabilistic decision-making, but few have systematically investigated the neural representations of the two objective attributes of probabilistic rewards, that is, the reward amount and the probability. Specifically, whether there are common or distinct neural activity patterns to represent the objective attributes and their association with the neural representation of the subjective valuation remains largely underexplored. We conducted two studies (nStudy1 = 34, nStudy2 = 41) to uncover distributed neural representations of the objective attributes and subjective value as well as their association with individual probability discounting rates. The amount and probability were independently manipulated to better capture brain signals sensitive to these two attributes and were presented simultaneously in Study 1 and successively in Study 2. Both univariate and multivariate pattern analyses showed that the brain activities in the superior parietal lobule (SPL), including the postcentral gyrus, were modulated by the amount of rewards and probability in both studies. Further, representational similarity analysis revealed a similar neural representation between these two objective attributes and between the attribute and valuation. Moreover, the SPL tracked the subjective value integrated by the hyperbolic function. Probability-related brain activations in the inferior parietal lobule were associated with the variability in individual discounting rates. These findings provide novel insights into a similar neural representation of the two attributes during probabilistic decision-making and perhaps support the common neural coding of stimulus objective properties and subjective value in the field of probabilistic discounting.

Reactivity of the ventromedial prefrontal cortex, but not the amygdala, to negative emotion faces predicts greed personality trait.

This study explored whether amygdala reactivity predicted the greed personality trait (GPT) using both task-based and resting-state functional connectivity analyses (ntotal = 452). In Cohort 1 (n = 83), task-based functional magnetic resonance imaging (t-fMRI) results from a region-of-interest (ROI) analysis revealed no direct correlation between amygdala reactivity to fearful and angry faces and GPT. Instead, whole-brain analyses revealed GPT to robustly negatively vary with activations in the right ventromedial prefrontal cortex (vmPFC), supramarginal gyrus, and angular gyrus in the contrast of fearful + angry faces > shapes. Moreover, task-based psychophysiological interaction (PPI) analyses showed that the high GPT group showed weaker functional connectivity of the vmPFC seed with a top-down control network and visual pathways when processing fearful or angry faces compared to their lower GPT counterparts. In Cohort 2, resting-state functional connectivity (rs-FC) analyses indicated stronger connectivity between the vmPFC seed and the top-down control network and visual pathways in individuals with higher GPT. Comparing the two cohorts, bilateral amygdala seeds showed weaker associations with the top-down control network in the high group via PPI analyses in Cohort 1. Yet, they exhibited distinct rs-FC patterns in Cohort 2 (e.g., positive associations of GPT with the left amygdala-top-down network FC but negative associations with the right amygdala-visual pathway FC). The study underscores the role of the vmPFC and its functional connectivity in understanding GPT, rather than amygdala reactivity.

Neural representations of the amount and the delay time of reward in intertemporal decision making.

Numerous studies have examined the neural substrates of intertemporal decision-making, but few have systematically investigated separate neural representations of the two attributes of future rewards (i.e., the amount of the reward and the delay time). More importantly, no study has used the novel analytical method of representational connectivity analysis (RCA) to map the two dimensions' functional brain networks at the level of multivariate neural representations. This study independently manipulated the amount and delay time of rewards during an intertemporal decision task. Both univariate and multivariate pattern analyses showed that brain activity in the dorsomedial prefrontal cortex (DMPFC) and lateral frontal pole cortex (LFPC) was modulated by the amount of rewards, whereas brain activity in the DMPFC and dorsolateral prefrontal cortex (DLPFC) was modulated by the length of delay. Moreover, representational similarity analysis (RSA) revealed that even for the regions of the DMPFC that overlapped between the two dimensions, they manifested distinct neural activity patterns. In terms of individual differences, those with large delay discounting rates (k) showed greater DMPFC and LFPC activity as the amount of rewards increased but showed lower DMPFC and DLPFC activity as the delay time increased. Lastly, RCA suggested that the topological metrics (i.e., global and local efficiency) of the functional connectome subserving the delay time dimension inversely predicted individual discounting rate. These findings provide novel insights into neural representations of the two attributes in intertemporal decisions, and offer a new approach to construct task-based functional brain networks whose topological properties are related to impulsivity.

The effects of single and a combination of determinants of anaemia in the very old: results from the TULIPS consortium.

BACKGROUND AND OBJECTIVES: Nutritional deficiencies, renal impairment and chronic inflammation are commonly mentioned determinants of anaemia. The aim of this study was to investigate the effects of these determinants, singly and in combination, on anaemia in the very old. METHOD: The TULIPS Consortium consists of four population-based studies in oldest-old individuals: Leiden 85-plus Study, LiLACS NZ, Newcastle 85+ study, and TOOTH. Five selected determinants (iron, vitamin B12, and folate deficiency; low estimated glomerular filtration rate (eGFR); and high C-reactive protein (CRP)) were summed. This sum score was used to investigate the association with the presence and onset of anaemia (WHO definition). The individual study results were pooled using random-effects models. RESULTS: In the 2216 participants (59% female, 30% anaemia) at baseline, iron deficiency, low eGFR and high CRP were individually associated with the presence of anaemia. Low eGFR and high CRP were individually associated with the onset of anaemia. In the cross-sectional analyses, an increase per additional determinant (adjusted OR 2.10 (95% CI 1.85-2.38)) and a combination of ≥2 determinants (OR 3.44 (95% CI 2.70-4.38)) were associated with the presence of anaemia. In the prospective analyses, an increase per additional determinant (adjusted HR 1.46 (95% CI 1.24-1.71)) and the presence of ≥2 determinants (HR 1.95 (95% CI 1.40-2.71)) were associated with the onset of anaemia. CONCLUSION: Very old adults with a combination of determinants of anaemia have a higher risk of having, and of developing, anaemia. Further research is recommended to explore causality and clinical relevance.

The impact of aging and reaching movements on grip stability control during manual precision tasks.

BACKGROUND: Operating an object by generating stable hand-grip force during static or dynamic posture control of the upper extremities simultaneously is an important daily activity. Older adults require different attentional resources during grip strength control and arm movements. However, the impact of aging and reaching movements on precise grip strength and stability control among older adults is not well understood. This study investigated the impact of aging and reaching movements on grip strength and stability control in both hands of the upper extremities. METHODS: Fifty healthy young adults (age: 28.8 ± 14.0 years) and 54 healthy older adults (73.6 ± 6.3 years) were recruited to perform isometric grip strength test at 20% maximal voluntary contraction as the target force during three manual precision tasks simultaneously: stationary task (without arm movements), forward-reach task, and backward-reach task. The average grip force (in kg) and coefficient of variation values (expressed as a percentage) during manual precision tasks were calculated to determine the quality of participants' grip strength. The deviation error, absolute error, and force-stability index values were calculated to determine the strength control relative to the target force. RESULTS: For both the young and older groups, the force-stability index values in both hands were significantly higher during forward- and backward-reaching movements than in the stationary condition (p < 0.05). The older group exhibited a significantly lower hand-grip strength and stability of strength control in both hands than the young group (p < 0.05). CONCLUSIONS: Aging and reaching task performance reduced the grip strength of participants and increased the variations in strength control of both hands relative to the target force, indicating that older adults exhibit poor grip strength and stability control when performing arm-reaching movements. These findings may help clinical therapists in establishing objective indexes for poor grip-stability control screening and developing appropriate rehabilitation programs or health-promotion exercises that can improve grip strength and stability control in older people.

Greed personality trait links to negative psychopathology and underlying neural substrates.

Greed personality trait (GPT), characterized by the desire to acquire more and the dissatisfaction of never having enough, has been hypothesized to link with negative emotion/affect characteristics and aggressive behaviors. To describe its emotion-related features, we utilized a series of scales to measure corresponding emotion/affect and aggression (n = 411) and collected their neuroimaging data (n = 330) to explore underlying morphological substrates. Correlational analyses revealed that greedy individuals show more negative symptoms (e.g. depression, loss of interest, negative affect), lower psychological well-being and more aggression. Mediation analyses further demonstrated that negative symptoms and psychological well-being mediated greedy individuals' aggression. Moreover, exploratory factor analysis extracted factor scores across three factors (negative psychopathology, happiness, and motivation) from the measures scales. Negative psychopathology and happiness remained robust mediators. Importantly, these findings were replicated in an independent sample (n = 68). Voxel-based morphometry analysis also revealed that gray matter volumes (GMVs) in the prefrontal-parietal-occipital system were associated with negative psychopathology and happiness, and GMVs in the frontal pole and middle frontal cortex mediated the relationships between GPT and aggressions. These findings provide novel insights into the negative characteristics of dispositional greed, and suggest their mediating roles on greedy individuals' aggression and underlying neuroanatomical substrates.

The medial temporal lobe structure and function support positive affect.

Positive affect (PA) is not only associated with individuals' psychological and physical health, but also their cognitive processes. However, whether medial temporal lobe (MTL) and its subfields' volume/functional connectivity can explain individual variability in PA remains understudied. We investigated the morphological (i.e., grey matter volume; GMV) and functional characteristics (i.e., resting-state functional connectivity; rsFC) of PA with a combination of univariate and multivariate pattern analyses (MVPA) using a large sample of participants (n = 321). We simultaneously collected the T1-weighted (n = 321), high-resolution MTL T2-weighted, and resting-state functional imaging data (n = 209). The MTL and its subfields' volumes, including the CA1, CA2+3, DG, and subiculum (SUB), perirhinal cortex (PRC), and parahippocampus (PHC), were extracted using an automatic segmentation of hippocampal subfields (ASHS) software. The morphological results revealed that GMVs in the prefrontal-occipital and limbic (i.e., hippocampus, amygdala, and PHC) systems were associated with variability in PA at the whole-brain level using MVPA but not univariate analysis. Linear regression results further revealed a positive association between the MTL subfields' GMV, especially for the right PRC, and PA after controlling for several covariates. PRC-seed-based rsFC analyses further revealed that its couplings with the fronto-parietal-occipital system predicted PA in both univariate and MVPA. These findings provide novel insights into the neuroanatomical and functional substrates underlying human PA trait. Findings also suggest critical contributions of the MTL and its subfield of the perirhinal cortex, but not hippocampal subfields, as well as its functional coupling with the fronto-parietal control-system on the formation of PA.

Comparison of Mitochondrial Adenosine Triphosphate-Sensitive Potassium Channel High- vs Low-Affinity Sulfonylureas and Cardiovascular Outcomes in Patients With Type 2 Diabetes Treated With Metformin.

Importance: Sulfonylureas are frequently used as add-on to metformin in type 2 diabetes (T2D), and individual sulfonylurea agents carry different risks of cardiovascular disease. Sulfonylureas' different affinities to cardiac mitochondrial adenosine triphosphate-sensitive potassium (mitoKATP) channels have been speculated to account for the intraclass difference in cardiovascular risk from in vitro and ex vivo studies; however, this hypothesis has not been assessed in a general population with diabetes receiving sulfonylureas added to metformin. Objective: To compare the risk of myocardial infarction (MI), ischemic stroke, or cardiovascular death in patients with T2D treated with mitoKATP channel high-affinity sulfonylureas and low-affinity sulfonylureas as add-on to metformin. Design, Setting, and Participants: This is a new-user, active-comparator, and propensity score-matched cohort study with analysis of the Taiwanese Diabetes Mellitus Health Database from 2006, to 2017. Data analysis was performed from August 2020 to July 2021. Exposures: Cardiac mitoKATP channel high-affinity (glyburide and glipizide) and low-affinity (gliclazide and glimepiride) sulfonylureas combined with metformin. Main Outcomes and Measures: Primary outcome was major adverse cardiovascular events (MACEs), a composite of cardiovascular death or hospitalization for either MI or ischemic stroke. Secondary outcomes included individual MACE components, heart failure, arrhythmia, all-cause mortality, and severe hypoglycemia. Cox proportional hazards models were used to estimate adjusted hazard ratios (aHRs). Results: Each sulfonylurea group comprised 53 714 patients (mean [SD] age, 54.7 [12.1] years; 31 962 men [59.5%]). MitoKATP channel high-affinity sulfonylureas vs low-affinity sulfonylureas when combined with metformin were associated with an increased risk of MACE (aHR, 1.18; 95% CI, 1.03-1.34), MI (aHR, 1.34; 95% CI, 1.04-1.73), all-cause mortality (aHR, 1.27; 95% CI, 1.03-1.57), and severe hypoglycemia (aHR, 1.82; 95% CI, 1.58-2.10), but not with increased risks of ischemic stroke, cardiovascular death, arrhythmia, and heart failure. The duration analyses revealed the highest MACE risk during 1 to 90 days after initiation of mitoKATP channel high-affinity sulfonylureas (aHR, 6.06; 95% CI, 4.86-7.55). Conclusions and Relevance: Use of mitoKATP channel high-affinity sulfonylureas vs low-affinity sulfonylureas was associated with an increased MACE risk in patients with T2D concomitantly receiving metformin, suggesting that high-affinity blockage of the mitoKATP channels could account for sulfonylurea-associated MACEs.

Association Between Specificity of Sulfonylureas to Cardiac Mitochondrial KATP Channels and the Risk of Major Adverse Cardiovascular Events in Type 2 Diabetes.

OBJECTIVE: Previous studies have revealed an intraclass difference in major adverse cardiovascular events (MACE) among sulfonylureas. In vitro and ex vivo studies reported several sulfonylureas to exhibit high-affinity blockage of cardiac mitochondrial ATP-sensitive potassium (mitoKATP) channels and could interfere with ischemic preconditioning, the most important mechanism of self-cardiac protection. However, no studies have examined whether these varying binding affinities of sulfonylureas could account for their intraclass difference in MACE. We compared mitoKATP channel high-affinity versus low-affinity sulfonylureas regarding the MACE risk in real-world settings. RESEARCH DESIGN AND METHODS: Using the Taiwan nationwide health care claims database, patients with type 2 diabetes initiating sulfonylurea monotherapy between 2007 and 2016 were included in the cohort study. A total of 33,727 new mitoKATP channel high-affinity (glyburide and glipizide) and low-affinity (gliclazide and glimepiride) sulfonylurea users, respectively, were identified after 1:1 propensity score matching. Cox proportional hazard models were used to estimate adjusted hazard ratios (aHRs) and 95% CI. RESULTS: MitoKATP channel high-affinity sulfonylureas were associated with a significantly increased risk of three-point MACE (aHR 1.21 [95% CI 1.03-1.44]), ischemic stroke (aHR 1.23 [95% CI 1.02-1.50]), and cardiovascular death (aHR 2.61 [95% CI 1.31-5.20]), but not with that of myocardial infarction (aHR 1.04 [95% CI 0.75-1.46]). The duration-response analyses revealed the highest MACE risk to be within 90 days of therapy (aHR 4.67 [95% CI 3.61-6.06]). CONCLUSIONS: Cardiac mitoKATP channel high-affinity sulfonylureas were associated with an increased MACE risk compared with low-affinity sulfonylureas in a nationwide population with diabetes.

Sex-specific static and dynamic functional networks of sub-divisions of striatum linking to the greed personality trait.

The study of greed has been broadly investigated and discussed in the field of social sciences, including economics, political science, and psychology. However, the neural mechanisms underlying greed personality trait (GPT) have received little attention from the cognitive neuroscience field and still remain unclear. In this study, we explored the associations between GPT and static/dynamic reward circuit-specifically its sub-regions' functional networks including caudate, nucleus accumbens (NAcc), and putamen. Behavioral analyses revealed significant associations of GPT with Past-Negative and Present-Fatalistic time attitude as well as attention impulsivity. Imaging analyses revealed a significant interaction effect between sex and GPT on the static reward functional networks. In particular, GPT was positively correlated with static caudate-NAcc, caudate-cerebellum, and NAcc-parahippocampus/medial orbitofrontal cortex (PHG/mOFC) for males but negatively correlated for females. GPT was also marginally and negatively correlated with static putamen-occipital pole functional connectivities among males. Interestingly, sex difference interaction patterns were further observed in the dynamic reward functional networks. Further, dynamic reward functional networks also exhibited some specific characteristics, manifesting in more brain regions involved for greedy behaviors. These findings suggest sex-specific static and dynamic functional networks underlying human dispositional greed, and also implicate the critical contributions of reward circuit, especially for sub-circuits of reward, on greed.

Neuroanatomical and functional substrates of the greed personality trait.

Greedy individuals often exhibit more impulsive decision-making and short-sighted behaviors. It has been assumed that altered reward circuitry and prospection network is associated with greed personality trait (GPT). In this study, we first explored the morphological characteristics (i.e., gray matter volume; GMV) of GPT combined with univariate and multivariate pattern analysis (MVPA) approaches. Second, we adopted a revised version of inter-temporal choice task and independently manipulated the amount and delay time of future rewards. Using brain-imaging design, reward- and prospection-related brain activations were assessed and their associations with GPT were further examined. The MVPA results showed that GPT was associated with the GMVs in the right lateral frontal pole cortex, left ventromedial prefrontal cortex, right lateral occipital cortex, and right occipital pole. Additionally, we observed that the amount-relevant brain activations (responding to reward circuitry) in the lateral orbitofrontal cortex were negatively associated with individual's variability in GPT scores, whereas the delay time-relevant brain activations (responding to prospection network system) in the dorsolateral prefrontal cortex, dorsomedial prefrontal cortex, superior parietal lobule, and anterior cingulate cortex were positively associated with individual's variability in GPT scores. These findings not only provide novel insights into the neuroanatomical substrates underlying the human dispositional greed, but also suggest the critical roles of reward and prospection processing on the greed.

Influence of aging and visual feedback on the stability of hand grip control in elderly adults.

Aging causes a gradual decrease in maximal grip strength and leads many elderly people to have to rely on visual feedback to compensate for poorer muscle strength in performing daily activities and preventing accidents. Previous studies have investigated age and visual feedback-related changes in grip strength. However, little is known about methods of determining the quality and stability of hand grip strength control in the elderly, which is important for understanding their ability to generate grip force when handling objects with and without visual feedback in daily living. Therefore, the purpose of this study was to investigate the influence of aging and visual feedback on the stability of hand grip control in both hands in elderly adults. Forty-four healthy elderly persons (age 80.5 ±â€¯4.53 years) and 36 young adults (age 32.69 ±â€¯16.48 years) were recruited to execute grip force stability tasks using both hands at a 2 kg target force level. To perform the grip force stability task, the participants were asked to hold the dynamometer tightly in an attempt to achieve the target force level under visual and non-visual feedback conditions. Strength performances (grip force and coefficient of variation values) and stability of strength control (deviation error, variation error and force stability index values) for hand grip force stability tasks were calculated and analyzed. Compared with the visual feedback condition, the stability of grip force control in the hands of the young and elderly groups were significantly reduced in the non-visual feedback condition by 23.5%-57.1% (p < .05). The elderly group also showed significantly worse hand grip strength performances and stability of hand strength control than the young adult group (p < .05). Aging and non-visual feedback reduced the hand grip force output and stability of grip strength control of the hands. This may reveal the difficulty with manipulating hand-held objects in the absence of visual feedback while performing activities of daily living among the elderly.