A neurocomputational account of self-other distinction: from cell to society

Human social systems are unique in the animal kingdom. Social norms, constructed at a higher level of organisation, influence individuals across vast spatiotemporal scales. Characterising the neurocomputational processes that enable the emergence of these social systems could inform holistic models of human cognition and mental illness. Social neuroscience has shown that the processing of ‘social’ information demands many of the same computations as those involved in reasoning about inanimate objects in ‘non-social’ contexts. However, for people to reason about each other’s mental states, the brain must be able to distinguish between one mind and another. This ability, to attribute a mental state to a specific agent, has long been studied by philosophers under the guise of ‘meta-representation’. Empathy research has taken strides in describing the neural correlates of representing another person’s affective or bodily state, as distinct from one’s own. However, Self-Other distinction in beliefs, and hence meta-representation, has not figured in formal models of cognitive neuroscience. Here, I introduce a novel behavioural paradigm, which acts as a computational assay for Self-Other distinction in a cognitive domain. The experiments in this thesis combine computational modelling with magnetoencephalography and functional magnetic resonance imaging to explore how basic units of computation, predictions and prediction errors, are selectively attributed to Self and Other, when subjects have to simulate another agent’s learning process. I find that these low-level learning signals encode information about agent identity. Furthermore, the fidelity of this encoding is susceptible to experience-dependent plasticity, and predicts the presence of subclinical psychopathological traits. The results suggest that the neural signals generating an internal model of the world contain information, not only about ‘what’ is out there, but also about ‘who’ the model belongs to. That this agent-specificity is learnable highlights potential computational failure modes in mental illnesses with an altered sense of Self

Technology, Science and Culture

From the success of the first and second volume of this series, we are enthusiastic to continue our discussions on research topics related to the fields of Food Science, Intelligent Systems, Molecular Biomedicine, Water Science, and Creation and Theories of Culture. Our aims are to discuss the newest topics, theories, and research methods in each of the mentioned fields, to promote debates among top researchers and graduate students and to generate collaborative works among them

Evolutionary computing techniques to aid the acquisition and analysis of nuclear magnetic resonance data

Evolutionary computation, including genetic algorithms and genetic programming have taken the ideas of evolution in biology and applied some of the characteristics to problem solving. The survival of the fittest paradigm allows a population of candidate solutions to be modified by sexual and asexual reproduction and mutation to come closer to solving the problem in question without the necessity of having prior knowledge of what a good solution looks like. The increasing importance of Nuclear Magnetic Resonance Spectroscopy in medicine has created a demand for automated data analysis for tissue classification and feature selection. The use of artificial intelligence techniques such as evolutionary computing can be used for such data analysis. This thesis applies the techniques of evolutionary computation to aid the collection and classification of Nuclear Magnetic Resonance spectroscopy data. The first section (chapters one and two) introduces Nuclear Magnetic Resonance spectroscopy and evolutionary computation and also contains a review of relevant literature. The second section focuses on classification. In the third chapter classification into two classes of brain tumours is undertaken. The fourth chapter expands this to classify tumours and tissues into more than two classes. Genetic Programming provided good solutions with relatively simple biochemical interpretation and was able to classify data into more than two classes at one time. The third section of the thesis concentrates on using evolutionary computation techniques to optimise data acquisition parameters directly from the Nuclear Magnetic Resonance hardware. Chapter five shows that Genetic Algorithms in particular are successful at suppressing signals from solvent while chapter six applies these techniques to find a way of enhancing the signals from metabolites important to the classification of brain tumours as found in chapter three. The final chapter draws conclusions as to the efficacy of evolutionary computation techniques applied to Nuclear Magnetic Resonance Spectroscop

Information Assurance through Binary Vulnerability Auditing

The goal of this research is to develop improved methods of discovering vulnerabilities in software. A large volume of software, from the most frequently used programs on a desktop computer, such as web browsers, e-mail programs, and word processing applications, to mission-critical services for the space shuttle, is unintentionally vulnerable to attacks and thus insecure. By seeking to improve the identification of vulnerabilities in software, the security community can save the time and money necessary to restore compromised computer systems. In addition, this research is imperative to activities of national security such as counterterrorism. The current approach involves a systematic and complete analysis of the low-level organization of software systems in stark contrast to existing approaches which are either ad-hoc or unable to identify all buffer overflow vulnerabilities. The scope of this project is to develop techniques for identifying buffer overflows in closed-source software where only the software’s executable code is available. These techniques use a comprehensive analysis of the software system’s flow of execution called binary vulnerability auditing. Techniques for binary vulnerability auditing are grounded in science and, while unproven, are more complete than traditional ad-hoc approaches. Since there are several attack vectors in software, this research will focus on buffer overflows, the most common class of vulnerability

Technological developments allowing for the widespread clinical adoption of proton radiotherapy

External beam radiation therapy using accelerated protons has undergone significant development since the first patients were treated with accelerated protons in 1954. Widespread adoption of proton therapy is now taking place and is fully justified based on early clinical and technical research and development. Two of the main advantages of proton radiotherapy are improved healthy tissue sparing and increased dose conformation. The latter has been improved dramatically through the clinical realization of Pencil Beam Scanning (PBS). Other significant advancements in the past 30 years have also helped to establish proton radiotherapy as a major clinical modality in the cancer-fighting arsenal. Proton radiotherapy technologies are constantly evolving, and several major breakthroughs have been accomplished which could allow for a major revolution in proton therapy if clinically implemented. In this thesis, I will present research and innovative developments that I personally initiated or participated in that brought proton radiotherapy to its current state as well as my ongoing involvement in leading research and technological developments which will aid in the mass adoption of proton radiotherapy. These include beam dosimetry, patient positioning technologies, and creative methods that verify the Monte Carlo dose calculations which are now used in proton treatment planning. I will also discuss major technological advances concerning beam delivery that should be implemented clinically and new paradigms towards patient positioning. Many of these developments and technologies can benefit the cancer patient population worldwide and are now ready for mass clinical implementation. These developments will improve proton radiotherapy efficiencies and further reduce the cost of proton therapy facilities. This thesis therefore reflects my historical and ongoing efforts to meet market costs and time demands so that the clinical benefit of proton radiotherapy can be realized by a more significant fraction of cancer patients worldwide

Radiobiology Textbook:Space Radiobiology

The study of the biologic effects of space radiation is considered a “hot topic,” with increased interest in the past years. In this chapter, the unique characteristics of the space radiation environment will be covered, from their history, characterization, and biological effects to the research that has been and is being conducted in the field. After a short introduction, you will learn the origin and characterization of the different types of space radiation and the use of mathematical models for the prediction of the radiation doses during different mission scenarios and estimate the biological risks due to this exposure. Following this, the acute, chronic, and late effects of radiation exposure in the human body are discussed before going into the detailed biomolecular changes affecting cells and tissues, and in which ways they differ from other types of radiation exposure. The next sections of this chapter are dedicated to the vast research that has been developed through the years concerning space radiation biology, from small animals to plant models and 3D cell cultures, the use of extremophiles in the study of radiation resistance mechanisms to the importance of ground-based irradiation facilities to simulate and study the space environment

2012 IMSAloquium, Student Investigation Showcase

Through SIR and its partnerships, IMSA students engage in rich opportunities to pursue compelling questions of interest, conduct investigations, engage with extraordinary advisors, communicate findings, and ultimately impact society.https://digitalcommons.imsa.edu/archives_sir/1004/thumbnail.jp

Case series of breast fillers and how things may go wrong: radiology point of view

INTRODUCTION: Breast augmentation is a procedure opted by women to overcome sagging breast due to breastfeeding or aging as well as small breast size. Recent years have shown the emergence of a variety of injectable materials on market as breast fillers. These injectable breast fillers have swiftly gained popularity among women, considering the minimal invasiveness of the procedure, nullifying the need for terrifying surgery. Little do they know that the procedure may pose detrimental complications, while visualization of breast parenchyma infiltrated by these fillers is also deemed substandard; posing diagnostic challenges. We present a case series of three patients with prior history of hyaluronic acid and collagen breast injections. REPORT: The first patient is a 37-year-old lady who presented to casualty with worsening shortness of breath, non-productive cough, central chest pain; associated with fever and chills for 2-weeks duration. The second patient is a 34-year-old lady who complained of cough, fever and haemoptysis; associated with shortness of breath for 1-week duration. CT in these cases revealed non thrombotic wedge-shaped peripheral air-space densities. The third patient is a 37‐year‐old female with right breast pain, swelling and redness for 2- weeks duration. Previous collagen breast injection performed 1 year ago had impeded sonographic visualization of the breast parenchyma. MRI breasts showed multiple non- enhancing round and oval shaped lesions exhibiting fat intensity. CONCLUSION: Radiologists should be familiar with the potential risks and hazards as well as limitations of imaging posed by breast fillers such that MRI is required as problem-solving tool

Characterization of alar ligament on 3.0T MRI: a cross-sectional study in IIUM Medical Centre, Kuantan

INTRODUCTION: The main purpose of the study is to compare the normal anatomy of alar ligament on MRI between male and female. The specific objectives are to assess the prevalence of alar ligament visualized on MRI, to describe its characteristics in term of its course, shape and signal homogeneity and to find differences in alar ligament signal intensity between male and female. This study also aims to determine the association between the heights of respondents with alar ligament signal intensity and dimensions. MATERIALS & METHODS: 50 healthy volunteers were studied on 3.0T MR scanner Siemens Magnetom Spectra using 2-mm proton density, T2 and fat-suppression sequences. Alar ligament is depicted in 3 planes and the visualization and variability of the ligament courses, shapes and signal intensity characteristics were determined. The alar ligament dimensions were also measured. RESULTS: Alar ligament was best depicted in coronal plane, followed by sagittal and axial planes. The orientations were laterally ascending in most of the subjects (60%), predominantly oval in shaped (54%) and 67% showed inhomogenous signal. No significant difference of alar ligament signal intensity between male and female respondents. No significant association was found between the heights of the respondents with alar ligament signal intensity and dimensions. CONCLUSION: Employing a 3.0T MR scanner, the alar ligament is best portrayed on coronal plane, followed by sagittal and axial planes. However, tremendous variability of alar ligament as depicted in our data shows that caution needs to be exercised when evaluating alar ligament, especially during circumstances of injury