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The processing of sequentially presented auditory information was investigated in Reading Delayed (RD) and Non-Reading Delayed (NRD) children through the use of middle latency event-related potentials (MERP's). MERP's from 16 4th and 5th grade RD children were compared to MERP's from 15 2nd and 3rd grade NRD children matched on intelligence and reading level. The children responded to a two tone behavioral sequencing task, then engaged in passive perception of a similar two tone sequence while MERP's were recorded for each tone. Various inter-stimulus intervals (ISI) were used in each task. On the behavioral sequencing task the NRD children performed better at all ISI's (F = 5.78, p $<$.03). MERP recordings from the RD group indicated a shorter latency of the Na waveform generated by the second stimulus at a 75 ms ISI compared to a 150 ms ISI (t = 4.66, p $<$.001) or a 500 ms ISI (t = 2.87, p $<$.01). Furthermore, the latency of the Na peak to the second stimulus was significantly and positively correlated to both groups' performance on the behavioral task, especially at the shortest ISI (r =.45; p $<$.006). These results are taken as an indication of a lack of normal inhibition in the RD group. When presented with a two tone sequence separated by short ISI's, the RD group failed to inhibit processing of the second tone, whereas at longer ISI's they responded in a manner similar to that of the NRD group. / Source: Dissertation Abstracts International, Volume: 52-08, Section: B, page: 4473. / Major Professor: Lloyd Elfner. / Thesis (Ph.D.)--The Florida State University, 1991.

Neurons code information about sensory stimuli temporally in the times of occurrence of action potentials as well as spatially in the joint discharge patterns of neurons within an ensemble. In this work, we present a framework for quantifying how well a particular stimulus feature is coded for a given stimulus regardless of whether the coding is temporal, spatial, or both. We develop a method for empirically quantifying response differences in terms of the Kullback-Leibler distance, an information-theoretic quantity related to classification error probabilities. A relationship between the Kullback-Leibler distance and Cramer-Rao bound allows quantification of the ultimate limits of an omniscient estimator to estimate stimulus parameters based on observation of a given ensemble's response. By studying these ultimate limits for the inputs and outputs of a neural ensemble we can quantify the processing and efficiency of the ensemble. We apply these techniques to single and multiple unit simulated data from the lateral superior olive (LSO), an auditory nucleus in cat that is responsive to the spatial location of sound. Our results support the view that the LSO is extracting azimuthal location information, but we also found that LSO outputs contain significant information pertaining to sound stimulus amplitude (loudness). The coding of these cues also has a temporal component; the early transient response tends to contain more information pertaining to stimulus amplitude than the sustained response, while both the sustained response and the transient response contain information pertaining to azimuthal location. Thus LSO responses multiplex information about both stimulus azimuth and amplitude in a time-varying manner. Our experiments with ensembles of LSO neurons suggest that extraction of stimulus angle and amplitude information by ensembles is more efficient when the ensembles are composed of different LSO unit types (fast and slow choppers) than when composed of homogeneous units.

This thesis presents the design of a digital speech transformation system for developing aids for the hearing impaired. The system is required to perform, in real time, four basic speech transformations: time-scale modification, frequency-scale modification, pitch modification, and spectral envelope modification. It is based on the sinusoidal representation of Quartieri and McAulay, but achieves the required deconvolution of the speech signal by liner prediction, rather than homomorphic filtering. / The system is implemented in software, and a detailed study is done to determine the type of hardware implementation required to perform the speech transformations in real time. The proposed implementation is a multiprocessor system based on the TMS320C25 digital signal processor. Results obtained on an emulator for the TMS320C25 demonstrate the ability of the system to analyze and synthesize the speech signal in real time, while results obtained by simulation demonstrate its transformation capabilities.

Thesis (Ph.D.)--Indiana University, Dept. of Psychology, 2005. / Source: Dissertation Abstracts International, Volume: 66-12, Section: B, page: 6941. Adviser: David B. Pisoni. Title from dissertation home page (viewed Oct. 11, 2006).

Noise is a major aggressor in the workplace. It is widely acknowledged that noise may be hazardous to health and may interfere with speech communication. Researchers have found that noise and noise-induced hearing loss can also compromise the audibility of warning signals. A computerized tool called "Detectsound" has been developed for predicting the capability of workers to detect auditory warning signals in noise and for providing an optimal adjustment of signal levels according to the functional limits of the target worker(s). This work represents a comprehensive revision and improvement over an earlier version of the "Detectsound" model [Laroche et al. (1991), Applied Acoustics, 32, 193--214]. The main enhanced features are: (1) taking into account the hearing status for individuals, (2) incorporating the normative data describing the effect of noise exposure and age on hearing thresholds (ISO 1999, ISO 7029), (3) integrating more recent and accurate data on frequency selectivity, and (4) improving the user interface for the implemented software program. (Abstract shortened by UMI.)

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