Functional magnetic resonance imaging : an intermediary between behavior and neural activity

Blood oxygen level dependent (BOLD) functional magnetic resonance imaging is a non-invasive technique used to trace changes in neural dynamics in reaction to mental activity caused by perceptual, motor or cognitive tasks. The BOLD response is a complex signal, a consequence of a series of physiological events regulated by increased neural activity. A method to infer from the BOLD signal onto underlying neuronal activity (hemodynamic inverse problem) is proposed in Chapter 2 under the assumption of a previously proposed mathematical model on the transduction of neural activity to the BOLD signal. Also, in this chapter we clarify the meaning of the neural activity function used as the input for an intrinsic dynamic system which can be viewed as an advanced substitute for the impulse response function. Chapter 3 describes an approach for recovering neural timing information (mental chronometry) in an object interaction decision task via solving the hemodynamic inverse problem. In contrast to the hemodynamic level, at the neural level, we were able to determine statistically significant latencies in activation between functional units in the model used. In Chapter 4, two approaches for regularization parameter tuning in a regularized-regression analysis are compared in an attempt to find the optimal amount of smoothing to be imposed on fMRI data in determining an empirical hemodynamic response function. We found that the noise autocorrelation structure can be improved by tuning the regularization parameter but the whitening-based criterion provides too much smoothing when compared to cross-validation. Chapter~5 illustrates that the smoothing techniques proposed in Chapter 4 can be useful in the issue of correlating behavioral and hemodynamic characteristics. Specifically, Chapter 5, based on the smoothing techniques from Chapter 4, seeks to correlate several parameters characterizing the hemodynamic response in Broca's area to behavioral measures in a naming task. In particular, a condition for independence between two routes of converting print to speech in a dual route cognitive model was verified in terms of hemodynamic parameters

Integrating online-offline interactions to explain societal challenges

Despite the wide literature on the consequences of Information and Communication Technologies (ICTs) use, the literature still lacks understanding about the societal consequences, positive or negative, intended or unintended. ICTs can yield the good and the bad. Consequences of technology usages on society are paradoxical. The paradoxical outcomes can be ta threat to the sustainability of society. Because interactions spread beyond the online space and its outcomes are paradoxical, societal challenges are complex problems. But not only complex problem, rather social complex problem. To harvest society, we need a better understanding of social complex problems. To do so, we adopted a multi-study dissertation model. To achieve that goal, the three studies of this doctoral work adopt a qualitative approach and a critical realist philosophy. This dissertation focuses on the societal implications of online phenomena that spillover offline. We look at a first case: The Arab Spring and aim at understanding how an online community that started on Facebook materialized in urban space, changing the political landscape (Study 2). Addressing these kind of contemporaneous events does not come without analytical challenges. Therefore, we use and extend a semiotic analytical tool to face the representational complexity of the data collected (Study 1) with a discussion of the underlying philosophical assumptions. Finally, online communities can also have social costs by providing an echo chamber to socially undesirable behaviors. We aim at offering a conceptual explanation of how these online interactions turn into offline behaviors with negative spillovers (Study 3)

Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS 1994), volume 1

The AIAA/NASA Conference on Intelligent Robotics in Field, Factory, Service, and Space (CIRFFSS '94) was originally proposed because of the strong belief that America's problems of global economic competitiveness and job creation and preservation can partly be solved by the use of intelligent robotics, which are also required for human space exploration missions. Individual sessions addressed nuclear industry, agile manufacturing, security/building monitoring, on-orbit applications, vision and sensing technologies, situated control and low-level control, robotic systems architecture, environmental restoration and waste management, robotic remanufacturing, and healthcare applications

ARTIFICIAL AGENTS MODELING FOR INTIMATE TELEPRESENCE

Ph.DDOCTOR OF PHILOSOPH

Actants, Agents, and Assemblages: Delivery and Writing in an Age of New Media

This dissertation redefines the rhetorical canon of delivery by drawing on interdisciplinary theories of technology and materiality, including hardware and software studies, assemblage theory, and actor-network theory. Rhetorical theorists and composition scholars have correctly equated the technological medium with delivery, but also have focused exclusively on the circulation of symbolic forces rather than the persuasive agency of technology itself, thus eliding the affordances and constraints posed by technological actors at the non-symbolic levels of hardware, software, protocol, and algorithms. I establish a historical precedent in classical theorists such as Demosthenes, Cicero, and Quintilian that acknowledges their understanding of the role of nonhuman actors in rhetoric. In contrast to contemporary views of an active human subject using a passive technological object to achieve a communicative aim, I extend these classical understandings of materiality by articulating a vision of technological agency where rhetorical agency and delivery are equally distributed across human and nonhuman actors and assemblages. This account of delivery enables rhetorical scholars to study how material artifacts and writing technologies circulate, transform, and affect rhetorical consequences as they enter into various associations and shape emergent political publics. Through new media case studies from activist newsgame designers and algorithmic art, I establish a form of multimodal public writing that reconceives of political community building in networked spaces as a process that necessarily involves the consideration of procedural, protocological, and algorithmic rhetorics and literacies. By examining how delivery occurs through a complex ecological and material milieu, I define a more nuanced theoretical framework that allows rhetoricians and composition theorists to more productively address the various non-symbolic aspects of digital rhetoric and nonhuman agency that increasingly serve as a condition of possibility for the ways we learn to write and communicate toda

1974/1975 UCI General Catalogue

General catalogue for the academic year 1974-1975

Automatic Derivation of Requirements for Components Used in Human-Intensive Systems

Human-intensive systems (HISs), where humans must coordinate with each other along with software and/or hardware components to achieve system missions, are increasingly prevalent in safety-critical domains (e.g., healthcare). Such systems are often complex, involving aspects such as concurrency and exceptional situations. For these systems, it is often difficult but important to determine requirements for the individual components that are necessary to ensure the system requirements are satisfied. In this thesis, we investigated an approach that employs interface synthesis methods developed for software systems to automatically derive such requirements for components used in HISs. In previous work, we investigated a requirement deriver that employs a regular language learning algorithm to iteratively refine the derived requirement based on counterexamples generated by model checking techniques. Since this learning-based requirement deriver often did not scale well, we investigated several learning and model checking optimizations. These optimizations significantly improved performance but affected the counterexample generation heuristics, often widely varying the permissiveness of the derived requirements. For comparison purposes, we investigated a direct requirement deriver that was purported to have poor performance but guarantees the derived requirements are adequately permissive, conceptually meaning the requirements are permissive as possible without violating the system requirements. For our evaluation, we applied these requirement derivers to case studies in two important domains, healthcare and election administration. Based on this evaluation, the direct requirement deriver with all optimizations applied had reasonable performance and ensures the derived requirements are adequately permissive. For the learning-based requirement deriver, many of the optimizations and heuristics have been presented previously, but we recommend how to selectively combine them to obtain reasonable performance while usually producing the adequately permissive derived requirements. Since such derived requirements often reflect the system complexity, these requirements can be easily misunderstood. Thus, we also investigated building views of the requirements that abstract away or highlight certain aspects to try to improve their understandability. Each single view appears to improve understandability and the multiple views seem to complement each other further improving understandability. Such derived requirements and their views can be used to safely develop and deploy the components used in HISs

Electro-anatomical models of the cochlear implant

Thesis (Ph. D.)--Harvard-MIT Division of Health Sciences and Technology, 2007.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Includes bibliographical references (p. 211-225).While cochlear implantation has become the standard care in treating patients with severe to profound sensorineural hearing loss, the variation in benefit (communicative ability) individual patients derive from implantation remains both large and, for the most part, unexplained. One explanation for this variation is the status of the implanted ear which, when examined histopathologically, also displays substantial variation due to both the pathogenesis of hearing loss (etiology, etc.) and pathological changes initiated by implantation. For instance, across-patient variation in electrode position and insertion depth is clearly present, as are differential amounts of residual spiral ganglion survival, fibrous tissue formation and electrode encapsulation, cochlear ossification, and idiosyncratic damage to adjacent cochlear structures. Because of the complex geometric electrical properties of the tissues found in the implanted ear, demonstrating the impact of pathological variability on neuronal excitation, and ultimately on behavioral performance, will likely require a detailed representation of the peripheral anatomy. Our approach has been to develop detailed, three-dimensional (3D) electro-anatomical models (EAMs) of the implanted ear capable of representing the aforementioned patient-specific types of pathological variation. In response to electric stimulation, these computational models predict an estimate of (1) the 3D electric field, (2) the cochleotopic pattern of neural activation, and (3) the electrically-evoked compound action potential (ECAP) recorded from intracochlear electrodes. This thesis focuses on three aims. First, two patient-specific EAMs are formulated from hundreds of digital images of the histologically-sectioned temporal bones of two patients, attempting to incorporate the detailed pathology of each. Second, model predictions are compared to relevant reports from the literature, data collected from a cohort of implanted research subjects, and, most importantly, to archival data collected during life from the same two patients used to derive our psychophysical threshold measures, and ECAP recordings) collectively show a promising correspondence between model-predicted and empirically-measured data. Third, by making incremental adjustments to the anatomical representation in the model, the impact of individual attributes are investigated, mechanisms that may degrade benefit suggested, and potential interventions explored.by Darren M. Whiten.Ph.D