The Neural Substrates of Multisensory Speech Perception

Comprehending speech is one of the most important human behaviors, but we are only beginning to understand how the brain accomplishes this difficult task. One key to speech perception seems to be that the brain integrates the independent sources of information available in the auditory and visual modalities in a process known as multisensory integration. This allows speech perception to be accurate, even in environments in which one modality or the other is ambiguous in the context of noise. Previous electrophysiological and functional magnetic resonance imaging (fMRI) experiments have implicated the posterior superior temporal sulcus (STS) in auditory-visual integration of both speech and non-speech stimuli. While evidence from prior imaging studies have found increases in STS activity for audiovisual speech compared with unisensory auditory or visual speech, these studies do not provide a clear mechanism as to how the STS communicates with early sensory areas to integrate the two streams of information into a coherent audiovisual percept. Furthermore, it is currently unknown if the activity within the STS is directly correlated with strength of audiovisual perception. In order to better understand the cortical mechanisms that underlie audiovisual speech perception, we first studied the STS activity and connectivity during the perception of speech with auditory and visual components of varying intelligibility. By studying fMRI activity during these noisy audiovisual speech stimuli, we found that STS connectivity with auditory and visual cortical areas mirrored perception; when the information from one modality is unreliable and noisy, the STS interacts less with the cortex processing that modality and more with the cortex processing the reliable information. We next characterized the role of STS activity during a striking audiovisual speech illusion, the McGurk effect, to determine if activity within the STS predicts how strongly a person integrates auditory and visual speech information. Subjects with greater susceptibility to the McGurk effect exhibited stronger fMRI activation of the STS during perception of McGurk syllables, implying a direct correlation between strength of audiovisual integration of speech and activity within an the multisensory STS.

NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.