An Uncertainty Visual Analytics Framework for Functional Magnetic Resonance Imaging

Improving understanding of the human brain is one of the leading pursuits of modern scientific research. Functional magnetic resonance imaging (fMRI) is a foundational technique for advanced analysis and exploration of the human brain. The modality scans the brain in a series of temporal frames which provide an indication of the brain activity either at rest or during a task. The images can be used to study the workings of the brain, leading to the development of an understanding of healthy brain function, as well as characterising diseases such as schizophrenia and bipolar disorder. Extracting meaning from fMRI relies on an analysis pipeline which can be broadly categorised into three phases: (i) data acquisition and image processing; (ii) image analysis; and (iii) visualisation and human interpretation. The modality and analysis pipeline, however, are hampered by a range of uncertainties which can greatly impact the study of the brain function. Each phase contains a set of required and optional steps, containing inherent limitations and complex parameter selection. These aspects lead to the uncertainty that impacts the outcome of studies. Moreover, the uncertainties that arise early in the pipeline, are compounded by decisions and limitations further along in the process. While a large amount of research has been undertaken to examine the limitations and variable parameter selection, statistical approaches designed to address the uncertainty have not managed to mitigate the issues. Visual analytics, meanwhile, is a research domain which seeks to combine advanced visual interfaces with specialised interaction and automated statistical processing designed to exploit human expertise and understanding. Uncertainty visual analytics (UVA) tools, which aim to minimise and mitigate uncertainties, have been proposed for a variety of data, including astronomical, financial, weather and crime. Importantly, UVA approaches have also seen success in medical imaging and analysis. However, there are many challenges surrounding the application of UVA to each research domain. Principally, these involve understanding what the uncertainties are and the possible effects so they may be connected to visualisation and interaction approaches. With fMRI, the breadth of uncertainty arising in multiple stages along the pipeline and the compound effects, make it challenging to propose UVAs which meaningfully integrate into pipeline. In this thesis, we seek to address this challenge by proposing a unified UVA framework for fMRI. To do so, we first examine the state-of-the-art landscape of fMRI uncertainties, including the compound effects, and explore how they are currently addressed. This forms the basis of a field we term fMRI-UVA. We then present our overall framework, which is designed to meet the requirements of fMRI visual analysis, while also providing an indication and understanding of the effects of uncertainties on the data. Our framework consists of components designed for the spatial, temporal and processed imaging data. Alongside the framework, we propose two visual extensions which can be used as standalone UVA applications or be integrated into the framework. Finally, we describe a conceptual algorithmic approach which incorporates more data into an existing measure used in the fMRI analysis pipeline

The Point of Political Belief

An intuitive and widely accepted view is that (a) beliefs aim at truth, (b) many citizens have stable and meaningful political beliefs, and (c) citizens choose to support political candidates or parties on the basis of their political beliefs. We argue that all three claims are false. First, we argue that political beliefs often differ from ordinary world-modelling beliefs because they do not aim at truth. Second, we draw on empirical evidence from political science and psychology to argue that most people lack stable and meaningful political beliefs. Third, we claim that the true psychological basis for voting behavior is not an individual’s political beliefs but rather group identity. Along the way, we reflect on what this means for normative democratic theory

Predicting Content Views Using Finite Integrals

Video hosting and sharing services enable creators and advertisers to create campaigns that engage viewers. To price the advertisements, and to give advertisers on the campaign an idea of the popularity of the content, the viewership is predicted. Both under- and over-prediction of views are associated with penalties, respectively of wasted inventory and capacity crunches. View estimations based on channel average suffer from sample bias and invisible trends. This disclosure describes techniques of in-flight view prediction, e.g., predictions of views done after the launch of a campaign for the remaining days of a campaign. The predictions of the total views on a line-up of in-flight videos are based on the distributions of prior view history. The described predictor delivers continuously improving predictions for live videos, and enables determination of whether a campaign is meeting view goals. It thereby enables real-time fine-tuning of inventory and capacity for the remaining days of the campaign

Exploration of virtual and augmented reality for visual analytics and 3D volume rendering of functional magnetic resonance imaging (fMRI) data

Statistical analysis of functional magnetic resonance imaging (fMRI), such as independent components analysis, is providing new scientific and clinical insights into the data with capabilities such as characterising traits of schizophrenia. However, with existing approaches to fMRI analysis, there are a number of challenges that prevent it from being fully utilised, including understanding exactly what a 'significant activity' pattern is, which structures are consistent and different between individuals and across the population, and how to deal with imaging artifacts such as noise. Interactive visual analytics has been presented as a step towards solving these challenges by presenting the data to users in a way that illuminates meaning. This includes using circular layouts that represent network connectivity and volume renderings with 'in situ' network diagrams. These visualisations currently rely on traditional 2D 'flat' displays with mouse-and-keyboard input. Due to the constrained screen space and an implied concept of depth, they are limited in presenting a meaningful, uncluttered abstraction of the data without compromising on preserving anatomic context. In this paper, we present our ongoing research on fMRI visualisation and discuss the potential for virtual reality (VR) and augmented reality (AR), coupled with gesture-based inputs to create an immersive environment for visualising fMRI data. We suggest that VR/AR can potentially overcome the identified challenges by allowing for a reduction in visual clutter and by allowing users to navigate the data abstractions in a 'natural' way that lets them keep their focus on the visualisations. We present exploratory research we have performed in creating immersive VR environments for fMRI data

Trauma-Associated Tinnitus: Audiological, Demographic and Clinical Characteristics

Background: Tinnitus can result from different etiologies. Frequently, patients report the development of tinnitus after traumatic injuries. However, to which extent this specific etiologic factor plays a role for the phenomenology of tinnitus is still incompletely understood. Additionally, it remains a matter of debate whether the etiology of tinnitus constitutes a relevant criterion for defining tinnitus subtypes. Objective: By investigating a worldwide sample of tinnitus patients derived from the Tinnitus Research Initiative (TRI) Database, we aimed to identify differences in demographic, clinical and audiological characteristics between tinnitus patients with and without preceding trauma. Materials: A total of 1,604 patients were investigated. Assessment included demographic data, tinnitus related clinical data, audiological data, the Tinnitus Handicap Inventory, the Tinnitus Questionnaire, the Beck Depression Inventory, various numeric tinnitus rating scales, and the World Health Organisation Quality of Life Scale (WHOQoL). Results: Our data clearly indicate differences between tinnitus patients with and without trauma at tinnitus onset. Patients suffering from trauma-associated tinnitus suffer from a higher mental burden than tinnitus patients presenting with phantom perceptions based on other or unknown etiologic factors. This is especially the case for patients with whiplash and head trauma. Patients with posttraumatic noise-related tinnitus experience more frequently hyperacousis, were younger, had longer tinnitus duration, and were more frequently of male gender. Conclusions: Trauma before tinnitus onset seems to represent a relevant criterion for subtypization of tinnitus. Patients with posttraumatic tinnitus may require specific diagnostic and therapeutic management. A more systematic and - at best - standardized assessment for hearing related sequelae of trauma is needed for a better understanding of the underlying pathophysiology and for developing more tailored treatment approaches as well.Fil: Kreuzer, Peter M.. Universitat Regensburg; AlemaniaFil: Landgrebe, Michael. Universitat Regensburg; AlemaniaFil: Schecklmann, Martin. Universitat Regensburg; AlemaniaFil: Staudinger, Susanne. Universitat Regensburg; AlemaniaFil: Langguth, Berthold. Universitat Regensburg; AlemaniaFil: Vielsmeier, Veronika. The TRI Database Study Group; AlemaniaFil: Kleinjung, Tobias. The TRI Database Study Group; AlemaniaFil: Lehner, Astrid. The TRI Database Study Group; AlemaniaFil: Poeppl, Timm B.. The TRI Database Study Group; AlemaniaFil: Figueiredo, Ricardo. The TRI Database Study Group; AlemaniaFil: Azevedo, Andréia. The TRI Database Study Group; AlemaniaFil: Binetti, Ana Carolina. The TRI Database Study Group; AlemaniaFil: Elgoyhen, Ana Belen. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Ingeniería Genética y Biología Molecular "Dr. Héctor N. Torres"; Argentina. The TRI Database Study Group; AlemaniaFil: Rates, Marcelo. The TRI Database Study Group; AlemaniaFil: Coelho, Claudia. The TRI Database Study Group; AlemaniaFil: Vanneste, Sven. The TRI Database Study Group; AlemaniaFil: de Ridder, Dirk. The TRI Database Study Group; AlemaniaFil: van de Heyning, Paul. The TRI Database Study Group; AlemaniaFil: Zeman, Florian. The TRI Database Study Group; AlemaniaFil: Mohr, Markus. The TRI Database Study Group; AlemaniaFil: Koller, Michael. The TRI Database Study Group; Alemani

A systematic review on incentive-driven mHealth technology: As used in diabetes management

Introduction Mobile Health (mHealth) technologies have been shown to improve self-management of chronic diseases, such as diabetes. However, mHealth tools, such as Apps, often have low rates of retention, eroding their potential benefits. Using incentives is a common mechanism for engaging and retaining patients that is applied by mHealth tools. We conducted a systematic review aiming to categorise the different types of incentive mechanisms employed in mHealth tools for diabetes management, which we defined as Incentive-driven Technologies (IDTs). As an auxiliary aim, we also analysed barriers to adoption of IDT technologies. Methods Literature published in English between January 2008 and August 2014 was identified through searching leading publishers and indexing databases: IEEE, Springer, Science Direct, NCBI, ACM, Wiley and Google Scholar. Results A total of 42 articles were selected. Of these, 34 presented mHealth tools with IDT mechanisms. Many of these contained more than one IDT, with Education the most common (n=21), followed by Reminder (n=11), Feedback (n=10), Social (n=8), Alert (n=5), Gamification (n=3), and Financial (n=2). The remaining 8 articles were review papers and a qualitative study of focus groups and interviews with patients with diabetes, where no new technologies were proposed, from which we defined barriers for adoption. Discussion We identified that while mHealth technologies have advanced over the last 5 years, the core IDT mechanisms have remained consistent. Instead, IDT mechanisms have evolved with the upgrades in technology, such as moving from manual to automatic content delivery and personalisation of content