Digital Signal Processing

Contains an introduction and reports on seventeen research projects.U.S. Navy - Office of Naval Research (Contract N00014-77-C-0266)Amoco Foundation FellowshipU.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)National Science Foundation (Grant ECS80-07102)U.S. Army Research Office (Contract DAAG29-81-K-0073)Hughes Aircraft Company FellowshipAmerican Edwards Labs. GrantWhitaker Health Sciences FundPfeiffer Foundation GrantSchlumberger-Doll Research Center FellowshipGovernment of Pakistan ScholarshipU.S. Navy - Office of Naval Research (Contract N00014-77-C-0196)National Science Foundation (Grant ECS79-15226)Hertz Foundation Fellowshi

Digital Signal Processing

Contains introduction and reports on seventeen research projects.U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)U.S. Navy - Office of Naval Research (Contract N00014-77-C-0266)National Science Foundation (Grant ECS80-07102)Bell Laboratories FellowshipAmoco Foundation FellowshipSchlumberger-Doll Research Center FellowshipSanders Associates, Inc.Toshiba Company FellowshipM.I.T. Vinton Hayes FellowshipHertz Foundation Fellowshi

Digital Signal Processing Group

Contains an introduction and reports on nineteen research projects.U.S. Navy - Office of Naval Research (Contract N00014-77-C-0266)U.S. Navy - Office of Naval Research (Contract N00014-81-K-0742)National Science Foundation (Grant ECS80-07102)Bell Laboratories FellowshipAmoco Foundation FellowshipU.S. Navy - Office of Naval Research (Contract N00014-77-C-0196)Schlumberger-Doll Research Center FellowshipToshiba Company FellowshipVinton Hayes FellowshipHertz Foundation Fellowshi

Digital Signal Processing

Contains summary of research and reports on sixteen research projects.U.S. Navy - Office of Naval Research (Contract N00014-75-C-0852)National Science Foundation FellowshipNATO FellowshipU.S. Navy - Office of Naval Research (Contract N00014-75-C-0951)National Science Foundation (Grant ECS79-15226)U.S. Navy - Office of Naval Research (Contract N00014-77-C-0257)Bell LaboratoriesNational Science Foundation (Grant ECS80-07102)Schlumberger-Doll Research Center FellowshipHertz Foundation FellowshipGovernment of Pakistan ScholarshipU.S. Navy - Office of Naval Research (Contract N00014-77-C-0196)U.S. Air Force (Contract F19628-81-C-0002)Hughes Aircraft Company Fellowshi

Uncertainty and Surprise Jointly Predict Musical Pleasure and Amygdala, Hippocampus, and Auditory Cortex Activity

Listening to music often evokes intense emotions [1, 2]. Recent research suggests that musical pleasure comes from positive reward prediction errors, which arise when what is heard proves to be better than expected [3]. Central to this view is the engagement of the nucleus accumbens—a brain region that processes reward expectations—to pleasurable music and surprising musical events [4, 5, 6, 7, 8]. However, expectancy violations along multiple musical dimensions (e.g., harmony and melody) have failed to implicate the nucleus accumbens [9, 10, 11], and it is unknown how music reward value is assigned [12]. Whether changes in musical expectancy elicit pleasure has thus remained elusive [11]. Here, we demonstrate that pleasure varies nonlinearly as a function of the listener’s uncertainty when anticipating a musical event, and the surprise it evokes when it deviates from expectations. Taking Western tonal harmony as a model of musical syntax, we used a machine-learning model [13] to mathematically quantify the uncertainty and surprise of 80,000 chords in US Billboard pop songs. Behaviorally, we found that chords elicited high pleasure ratings when they deviated substantially from what the listener had expected (low uncertainty, high surprise) or, conversely, when they conformed to expectations in an uninformative context (high uncertainty, low surprise). Neurally, we found using fMRI that activity in the amygdala, hippocampus, and auditory cortex reflected this interaction, while the nucleus accumbens only reflected uncertainty. These findings challenge current neurocognitive models of music-evoked pleasure and highlight the synergistic interplay between prospective and retrospective states of expectation in the musical experience

Remote access computed tomography colonography

This thesis presents a novel framework for remote access Computed Tomography Colonography (CTC). The proposed framework consists of several integrated components: medical image data delivery, 2D image processing, 3D visualisation, and feedback provision. Medical image data sets are notoriously large and preserving the integrity of the patient data is essential. This makes real-time delivery and visualisation a key challenge. The main contribution of this work is the development of an efficient, lossless compression scheme to minimise the size of the data to be transmitted, thereby alleviating transmission time delays. The scheme utilises prior knowledge of anatomical information to divide the data into specific regions. An optimised compression method for each anatomical region is then applied. An evaluation of this compression technique shows that the proposed ‘divide and conquer’ approach significantly improves upon the level of compression achieved using more traditional global compression schemes. Another contribution of this work resides in the development of an improved volume rendering technique that provides real-time 3D visualisations of regions within CTC data sets. Unlike previous hardware acceleration methods which rely on dedicated devices, this approach employs a series of software acceleration techniques based on the characteristic properties of CTC data. A quantitative and qualitative evaluation indicates that the proposed method achieves real-time performance on a low-cost PC platform without sacrificing any image quality. Fast data delivery and real-time volume rendering represent the key features that are required for remote access CTC. These features are ultimately combined with other relevant CTC functionality to create a comprehensive, high-performance CTC framework, which makes remote access CTC feasible, even in the case of standard Web clients with low-speed data connections