The Ellsberg 'Problem' and Implicit Assumptions under Ambiguity

Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In this study, we assessed normative models based on deep autoencoders using structural neuroimaging data from patients with Alzheimer’s disease (n = 206) and mild cognitive impairment (n = 354). We first trained the autoencoder on an independent dataset (UK Biobank dataset) with 11,034 healthy controls. Then, we estimated how each patient deviated from this norm and established which brain regions were associated to this deviation. Finally, we compared the performance of our normative model against traditional classifiers. As expected, we found that patients exhibited deviations according to the severity of their clinical condition. The model identified medial temporal regions, including the hippocampus, and the ventricular system as critical regions for the calculation of the deviation score. Overall, the normative model had comparable cross-cohort generalizability to traditional classifiers. To promote open science, we are making all scripts and the trained models available to the wider research community.

BackgroundPatterns of atrophy in the brain highly differ between individual Alzheimer’s Disease (AD) patients, however, most clinical research focuses on group‐level differences (Verdi et al., 2021). Here we used a novel technique, neuroanatomical normative modelling, to reveal individual patterns of cortical thickness by quantifying deviations from the normative range. We applied a hierarchical Bayesian regression (HBR) normative model (Kia et al., 2021), to amyloid‐positive AD patients who had clinical amyloid PET imaging at the Imperial Memory Clinic (IMC). Patients had either AD dementia or mild cognitive impairment due to AD. We hypothesised that there would be individual differences in patterns of cortical atrophy in these patients.MethodCortical thickness across 148 regions of interest (ROIs) was generated using FreeSurfer from n=130 (102 AD patients and 28 healthy controls) T1‐weighted MRIs acquired from the IMC. A reference HBR normative model was trained on a separate dataset of n=34,490 healthy individuals to index population variability, which predicted cortical thickness at each ROI using age and sex. This generated cortical thickness z‐scores for each ROI, per patient (z‐score < ‐1.96 = outlier).ResultThe patterns of cortical atrophy outliers were highly varied in amyloid‐positive AD patients. For instance, the largest proportion of outliers in a region was 60% within the superior temporal sulci, if atrophy were homogenous we would expect 100% of outliers to be here (Fig.1). This heterogeneity was also seen when comparing how similar outlier patterns were between patients (Fig.2). We also found that the proportions of outliers differ according to disease severity, e.g. the highest percentage of outliers was 70% within superior temporal sulci within the AD dementia subgroup, and 50% in superior temporal sulci in the mild cognitive impairment due to AD subgroup (Fig.3).ConclusionAmyloid‐positivity results in heterogenous patterns of cortical atrophy. This is more pronounced in AD dementia, though still present in people with mild cognitive impairment due to AD. Neuroanatomical normative maps have the potential to be individualised markers of disease, and with application to longitudinal data could track individual disease progression.

Normative modelling is a method for understanding the underlying heterogeneity within brain disorders like Alzheimer Disease (AD), by quantifying how each patient deviates from the expected normative pattern that has been learned from a healthy control distribution. Existing deep learning based normative models have been applied on only single modality Magnetic Resonance Imaging (MRI) neuroimaging data. However, these do not take into account the complementary information offered by multimodal M RI, which is essential for understanding a multifactorial disease like AD. To address this limitation, we propose a multi-modal variational autoencoder (mmVAE) based normative modelling framework that can capture the joint distribution between different modalities to identify abnormal brain volume deviations due to AD. Our multi-modal framework takes as input Freesurfer processed brain region volumes from T1-weighted (cortical and subcortical) and T2-weighed (hippocampal) scans of cognitively normal participants to learn the morphological characteristics of the healthy brain. The estimated normative model is then applied on AD patients to quantify the deviation in brain volumes and identify abnormal brain pattern deviations due to the progressive stages of AD. We compared our proposed mmVAE with a baseline unimodal VAE having a single encoder and decoder and the two modalities concatenated as unimodal input. Our experimental results show that deviation maps generated by mmVAE are more sensitive to disease staging within AD, have a better correlation with patient cognition and result in higher number of brain regions with statistically significant deviations compared to the unimodal baseline model.

The purpose of this study was to analyze the range of critiques of successful aging models and the suggestions for improvement as expressed in the social gerontology literature. We conducted a systematic literature review using the following criteria: journal articles retrieved in the Abstracts in Social Gerontology, published 1987-2013, successful aging/ageing in the title or text (n = 453), a critique of successful aging models as a key component of the article. Sixty-seven articles met the criteria. Qualitative methods were used to identify key themes and inductively configure meanings across the range of critiques. The critiques and remedies fell into 4 categories. The Add and Stir group suggested a multidimensional expansion of successful aging criteria and offered an array of additions. The Missing Voices group advocated for adding older adults' subjective meanings of successful aging to established objective measures. The Hard Hitting Critiques group called for more just and inclusive frameworks that embrace diversity, avoid stigma and discrimination, and intervene at structural contexts of aging. The New Frames and Names group presented alternative ideal models often grounded in Eastern philosophies. The vast array of criteria that gerontologists collectively offered to expand Rowe and Kahn's original successful model is symptomatic of the problem that a normative model is by definition exclusionary. Greater reflexivity about gerontology's use of "successful aging" and other normative models is needed.

This article evaluates the 3 general frames of reference used in analyzing the nonphysiologic origins of fertility differences: utility, normative, and drift. It is suggested that the drift model overcomes some of the limitations of the other 2 models and provides a closer approximation to behavioral realities. Implicit in the utility model is the assumption that people's behavior expresses their preferences amony available alternatives. It is further assumed that the individual has available a range of possible behaviors, means to the atgtainment of behavioral goals chosen, and reliable information concerning the likely consequences of a given choice. A weakness of this approach has been its rather parochial concentration on economic costs and benefits and its failure to take account of the ways these costs and benefits are differentially assessed and weighted by different populations. The normative model emphasizes the individual's group affiliations and social roles. A criticism of this model is that it ignores the possibility of conflict among the different norms associated with an individual's various roles or among interacting individuals such as husbands and wives. Together, the utility and normative models imply the existence of more conscious rationality in human behavior than may actually be the case. The 3rd model, drift, emphasizes the ongoing, developmental, incemental nature of human behavior. It posits a behavior that begins almost by accident at some point within the range of possible and allowable behaviors, then moves toward conslusion in a manner largely imperceptible to the actor. The idea of drift is compatible with the observation that social structures are constantly changed while at the same time providing the framework within which reproducing and changing behaviors can unfold. In contrast to the utility and normative models, which tend to be static, the drift model emphasizes both change and the manner in which change takes place.

Schizophrenia is associated with subtle brain structural alterations, but separating disease from medication effects is challenging. Antipsychotic dopamine D2 receptor (D2R) antagonism has been associated with striatal volume increases, but effects of partial D2R agonism by newer antipsychotics are largely unexplored. This study aimed to compare short-term brain changes associated with either D2R antagonism or partial D2R agonism using normative modeling. Secondarily, the study aimed to explore long-term effects following naturalistic treatment. Antipsychotic-naïve patients with first-episode psychosis received 6 weeks of monotherapy with either amisulpride (D2R antagonist) (N = 41) or aripiprazole (partial D2R agonist) (N = 45). All patients underwent structural magnetic resonance imaging before and after 6 weeks of treatment. A subset was re-scanned at 6 months, 1 year, and 2 years of naturalistic treatment. A pretrained normative model was applied to 186 subcortical and cortical regions. We used Wilcoxon signed-rank tests to identify longitudinal structural deviations. Amisulpride and aripiprazole were associated with striatal volume increases after 6 weeks. No cortical effects were observed with amisulpride. Thinning of the temporal lobe was observed with aripiprazole. After 6 months, and 1 and 2 years, the striatal changes abated but cortical thinning in the frontal lobes emerged. Both partial D2R agonism and D2R antagonism appear linked to striatal volume increases; however, changes appear transient. Conversely, frontal thinning occurs over time and appears less closely linked to antipsychotic treatment. Interpreting structural brain changes in patients with psychosis require consideration of short-term pharmacological effects as well as factors related to illness progression.

Capturing the Individual Deviations From Normative Models of Brain Structure for Depression Diagnosis and Treatment

The Choroid Plexus (ChP) is a vascular brain structure involved in vital brain functions. Most clinical studies have focused on analyzing ChP Volume (ChPV) in diseased populations, revealing a pattern of increased ChPV that might be related to neuroinflammatory processes. For full clinical translation, it is crucial to understand the normal variability of ChPV in relation to biological factors (such as age and gender) and brain anthropometric measures. Nonetheless, this has only been partially explored, and primarily in small size cohorts of healthy subjects. This study aims to develop and validate a normative modeling approach to describe the natural variation of ChPV across the adult lifespan. Age, gender, lateral ventricles volume, and total intracranial volume of 1,036 healthy subjects (age: 36-88 years) were used as independent regressors for a Bayesian hierarchical normative model, which was tested on two independent clinical cohorts of patients affected by depression (DEP) or multiple sclerosis (MS), respectively. The proposed model explains up to 40% of ChPV normal variability in healthy subjects and can detect ChPV alterations at the level of individual patients, replicating existing findings of altered ChPV in DEP and MS.Clinical Relevance- This work establishes a robust, portable normative benchmark for quantitative imaging of choroid plexus volume to be used as an individualized biomarker in neuroimaging studies, without additional collection of normative data.

BackgroundImproving dementia diagnosis is a major global concern, given that up to 20% of subjects are misdiagnosed. Normative modelling, which quantifies how far individuals deviate from healthy controls (HC), may help to better situate subjects along the spectrum. To determine whether this is the case, we implemented a deep learning based normative model and tested it on structural neuroimaging data from subjects with HC, mild cognitive impairment (MCI), and Alzheimer’s disease (AD).MethodWe developed an adversarial autoencoder (AAE) (Figure 1) leveraging FreeSurfer features, namely cortical surface area of 68 cortical subregions (34 by hemisphere; Desikan‐Killiany atlas) and volumes of 33 neuroanatomical structures (Aseg atlas). Our model not only returns individual “deviation” scores—divergence from HC—but also identifies regions of interest that contribute to said score, facilitating interpretability. We retrieved T1‐weighted MRI scans (n = 204) from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (HC/MCI/AD 105/29/60; Table 1). We trained our AAE on 71 HC samples (n = 71) and tested it on the rest (n = 133). We used bootstrapping to compute confidence intervals (CI) for each point estimate and examined regions where scores differed for the considered groups [1].ResultDeviation scores were lowest for HC (mean 0.74 [95%‐CI 0.63–0.88]), highest for AD (mean 1.21 [95%‐CI 1.03–1.50]), and intermediate for MCI (mean 1.04 [95%‐CI 0.88–1.27]), implying subjects indeed fell along the AD spectrum (Figure 2A). Said scores also enabled classifying subjects into HC, MCI, and AD with a mean area under the curve (AUC) of 75% (Figure 2B‐C; HC vs. MCI: 0.75 [95%‐CI 0.62–0.85]; HC vs. AD: 0.76 [95%‐CI 0.64–0.82]). According to the AAE, the hippocampus, parahippocampal cortex, ventricles, and inferior parietal lobe contributed to such differences (Figure 2D‐E).ConclusionNormative models can identify structures that become abnormal as the brain undergoes ageing and AD, in line with the literature. Further testing on a larger and more heterogeneous sample will reveal the potential of this tool and its potential deployment in clinics.

Products can consist of many sub-assemblies and small disturbances in the process can lead to larger negative effects downstream. Such variances in production are a challenge from a quality control and operational risk management perspective but also it distorts the assurance processes from an auditing perspective. To control production effectively waste needs to be taken into account in normative models, but this is complicated by cumulative effects. We developed an analytical normative model based on the bill of material, that derives the rejection rates from the underlying processes without direct measurement. The model enables improved analysis and prediction. If the rejection rate is not taken into account the function of the bill of material as a reference model deteriorates and therefore output measures become more opaque and harder to verify. As a consequence it is extremely difficult or even impossible to assess efficiency and effectiveness of operations. Secondly it is impossible to judge whether net salable assets represent the correct amount and finally it is impossible to assert whether the operations do comply to company standards and applicable laws.

The object of this study is to assess administrative reforms and change from the point of view of theoretical administrative models of hierarchical (traditional) administration, New Public Management (NPM), and New Public Governance (NPG) in Latvia, Lithuania, and Slovakia. Normative models offer a critique of legacy administrative practices; their wholesale implementation is seldom practical or successful. Reforms framed as “modernization” in these countries over the past three decades have generally followed the principles of NPM. Although policy arguments for introducing elements of NPG can be observed in the studied cases, the paper argues that NPG’s rhetorical attractiveness for resolving perceived shortcomings of other models lacks specific implementation mechanisms that would be viable within the existing institutional framework of the studied countries. Factors, such as the relatively small size of Latvia, Lithuania, and Slovakia, and obvious benefits of EU integration, appear to have moderated reforms to a point that core institutional features have become stable, and are also similar among the three countries: the dominance of hierarchical administrative model with rigid separation of powers structure and strong courts that can adjudicate administrative decisions, with numerous NPM inspired “modernization” measures, including the introduction of various interactive public services. The paper’s findings support the idea that Latvia, Lithuania, and Slovakia are administrative systems that have stable core governance institutions, and national public administrations modernize various aspects of their operation by introducing elements of NPM and NPG within the executive, but not reviewing the basic setup of these institutions. From this point of view, the findings are in line with the assumptions of the normative model of Neo-Weberian State (NWS)

One of the distinctive features of the post-Hegelian tradition of social philosophy is the connection it forges between normative criticism and historical understanding. This chapter discusses the normative models of work which are frameworks for normative criticism in this post-Hegelian sense. According to the first model, the instrumental model, the core norms of work are those of means-ends rationality. The second model, the expressive model, takes the core norms of work to be internal to working activity. According to the third model, the recognition model, the core norms of work concern with the norms that relate to individual achievement or contribution through work or the conditions that must in place for individuals to participate in the exchange of services by which market societies reproduce themselves. The appropriateness of a normative model of work depends in part on its responsiveness to the dominant social pathologies and malaises of work. Keywords:contemporary malaise; expressive model; instrumental model; normative models; post-Hegelian tradition; recognition model

A Decomposition-based Approach of Global Norms for Hierarchical Normative Systems

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

This paper discusses a principal---agent problem with multi-dimensional incomplete information between a principal and an agent. Firstly, how to describe the incomplete information in such agency problem is a challenging issue. This paper characterizes the incomplete information by uncertain variable, because it has been an appropriate tool to depict subjective assessment and model human uncertainty. Secondly, the relevant literature often used expected-utility-maximization to measure the two participators' goals. However, Ellsberg paradox indicates that expected utility criterion is not always appropriate to be regarded as decision rule. For this reason, this paper presents another decision rule based on confidence level. Instead of expected-utility-maximization, the principal's aim is to maximize his potential income under the acceptable confidence level, and the agent's aim depends on whether he has private information about his efforts. According to the agent's different decision rules, three classes of uncertain agency (UA) models and their respective optimal contracts are presented. Finally, a portfolio selection problem is studied to demonstrate the modeling idea and the viability of the proposed UA models.