Biology Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2749
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Item EFFECTS OF AGING ON MIDBRAIN AND CORTICAL SPEECH-IN-NOISE PROCESSING(2016) Presacco, Alessandro; Andreson, Samira; Simon, Jonathan Z.; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Older adults frequently report that they can hear what they have been told but cannot understand the meaning. This is particularly true in noisy conditions, where the additional challenge of suppressing irrelevant noise (i.e. a competing talker) adds another layer of difficulty to their speech understanding. Hearing aids improve speech perception in quiet, but their success in noisy environments has been modest, suggesting that peripheral hearing loss may not be the only factor in the older adult’s perceptual difficulties. Recent animal studies have shown that auditory synapses and cells undergo significant age-related changes that could impact the integrity of temporal processing in the central auditory system. Psychoacoustic studies carried out in humans have also shown that hearing loss can explain the decline in older adults’ performance in quiet compared to younger adults, but these psychoacoustic measurements are not accurate in describing auditory deficits in noisy conditions. These results would suggest that temporal auditory processing deficits could play an important role in explaining the reduced ability of older adults to process speech in noisy environments. The goals of this dissertation were to understand how age affects neural auditory mechanisms and at which level in the auditory system these changes are particularly relevant for explaining speech-in-noise problems. Specifically, we used non-invasive neuroimaging techniques to tap into the midbrain and the cortex in order to analyze how auditory stimuli are processed in younger (our standard) and older adults. We will also attempt to investigate a possible interaction between processing carried out in the midbrain and cortex.Item MEG, PSYCHOPHYSICAL AND COMPUTATIONAL STUDIES OF LOUDNESS, TIMBRE, AND AUDIOVISUAL INTEGRATION(2011) Jenkins III, Julian; Poeppel, David; Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Natural scenes and ecological signals are inherently complex and understanding of their perception and processing is incomplete. For example, a speech signal contains not only information at various frequencies, but is also not static; the signal is concurrently modulated temporally. In addition, an auditory signal may be paired with additional sensory information, as in the case of audiovisual speech. In order to make sense of the signal, a human observer must process the information provided by low-level sensory systems and integrate it across sensory modalities and with cognitive information (e.g., object identification information, phonetic information). The observer must then create functional relationships between the signals encountered to form a coherent percept. The neuronal and cognitive mechanisms underlying this integration can be quantified in several ways: by taking physiological measurements, assessing behavioral output for a given task and modeling signal relationships. While ecological tokens are complex in a way that exceeds our current understanding, progress can be made by utilizing synthetic signals that encompass specific essential features of ecological signals. The experiments presented here cover five aspects of complex signal processing using approximations of ecological signals : (i) auditory integration of complex tones comprised of different frequencies and component power levels; (ii) audiovisual integration approximating that of human speech; (iii) behavioral measurement of signal discrimination; (iv) signal classification via simple computational analyses and (v) neuronal processing of synthesized auditory signals approximating speech tokens. To investigate neuronal processing, magnetoencephalography (MEG) is employed to assess cortical processing non-invasively. Behavioral measures are employed to evaluate observer acuity in signal discrimination and to test the limits of perceptual resolution. Computational methods are used to examine the relationships in perceptual space and physiological processing between synthetic auditory signals, using features of the signals themselves as well as biologically-motivated models of auditory representation. Together, the various methodologies and experimental paradigms advance the understanding of ecological signal analytics concerning the complex interactions in ecological signal structure.Item Memory-related cognitive modulation of human auditory cortex: Magnetoencephalography-based validation of a computational model(2008-04-09) Rong, Feng; Contreras-Vidal, José L; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)It is well known that cognitive functions exert task-specific modulation of the response properties of human auditory cortex. However, the underlying neuronal mechanisms are not well understood yet. In this dissertation I present a novel approach for integrating 'bottom-up' (neural network modeling) and 'top-down' (experiment) methods to study the dynamics of cortical circuits correlated to shortterm memory (STM) processing that underlie the task-specific modulation of human auditory perception during performance of the delayed-match-to-sample (DMS) task. The experimental approach measures high-density magnetoencephalography (MEG) signals from human participants to investigate the modulation of human auditory evoked responses (AER) induced by the overt processing of auditory STM during task performance. To accomplish this goal, a new signal processing method based on independent component analysis (ICA) was developed for removing artifact contamination in the MEG recordings and investigating the functional neural circuits underlying the task-specific modulation of human AER. The computational approach uses a large-scale neural network model based on the electrophysiological knowledge of the involved brain regions to simulate system-level neural dynamics related to auditory object processing and performance of the corresponding tasks. Moreover, synthetic MEG and functional magnetic resonance imaging (fMRI) signals were simulated with forward models and compared to current and previous experimental findings. Consistently, both simulation and experimental results demonstrate a DMSspecific suppressive modulation of the AER and corresponding increased connectivity between the temporal auditory and frontal cognitive regions. Overall, the integrated approach illustrates how biologically-plausible neural network models of the brain can increase our understanding of brain mechanisms and their computations at multiple levels from sensory input to behavioral output with the intermediate steps defined.Item Auditory edge detection: the dynamics of the construction of auditory perceptual representations(2006-04-27) Chait, Maria; Poeppel, David; Simon, Jonathan Z; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation investigates aspects of auditory scene analysis such as the detection of a new object in the environment. Specifically I try to learn about these processes by studying the temporal dynamics of magnetic signals recorded from outside the scalp of human listeners, and comparing these dynamics with psychophysical measures. In total nine behavioral and Magneto-encephalography (MEG) brain-imaging experiments are reported. These studies relate to the extraction of tonal targets from background noise and the detection of change within ongoing sounds. The MEG deflections we observe between 50-200 ms post transition reflect the first stages of perceptual organization. I interpret the temporal dynamics of these responses in terms of activation of cortical systems that participate in the detection of acoustic events and the discrimination of targets from backgrounds. The data shed light on the statistical heuristics with which our brains sample, represent, and detect changes in the world, including changes that are not the immediate focus of attention. In particular, the asymmetry of responses to transitions between 'order' and 'disorder' within a stimulus can be interpreted in terms of different requirements for temporal integration. The similarity of these transition-responses with commonly observed onset M50 and M100 auditory-evoked fields allows us to suggest a hypothesis as to their underlying functional significance, which so far has remained unclear. The comparison of MEG and psychophysics demonstrates a striking dissociation between higher level mechanisms related to conscious detection and the lower-level, pre-attentive cortical mechanisms that sub-serve the early organization of auditory information. The implications of these data for the processes that underlie the creation of perceptual representations are discussed. A comparison of the behavior of normal and dyslexic subjects in a tone-in-noise detection task revealed a general difficulty in extracting tonal objects from background noise, manifested by a globally delayed detection speed, associated with dyslexia. This finding may enable us to tease apart the physiological and behavioral corollaries of these early, pre-attentive processes. In conclusion, the sum of these results suggests that the combination of behavioral and MEG investigative tools can provide new insights into the processes by which perceptual representations emerge from sensory input.