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 2008 Summer Research Fellowship

Kathleen Mettel
University of Illinois at Urbana-Champaign
Title: Complex Sound Representation in the Rat Ventral Auditory Field
Mentor: Pritesh K. Pandya, PhD, University of Illinois at Urbana-Champaign

Project Description: Current research is focusing on how sound is processed throughout the various levels of the auditory system. The auditory cortex is one of the higher levels in the hierarchy of auditory processing. Here, a primary field (AI) and multiple “belt fields” have been discovered using anatomical and physiological approaches. Many of these studies and overall knowledge of these belt fields warrants further study. The overall goal of this area of research is to understand how different fields represent sounds, from simple pure tones to complex sounds such as noise and even speech.

There are multiple techniques to study the functional organization of the auditory cortex. One of these techniques, microelectrode mapping, allows the experimenter to determine how individual neurons respond to different features of acoustic stimuli. This involves placing microelectrodes at many locations in the cortex and directly recording the response of neurons. These recording sites together form a “map” that shows how neurons respond within and across different cortical fields.

Some cortical fields are organized systematically on the basis of frequency gradient increasing from the posterior to the anterior parts of AI ( Polley et al, 2007; Pandya et al, 2007). Cortical responses differ within and across fields. Some neurons are broadly tuned responding to a wide range of frequencies. Neural latency is another property that can be quantified and compared. Al neurons respond much quicker to sound than the Posterior Auditory Field (PAF), for example suggesting a possible order of processing (Polley et al, 2007; Pandya et al, 2007; Doron et al, 2002). Another property used to differentiate fields is monotonicity, or the amount of firing as the intensity increases. Rate-level functions can show an increase (monotonic), leveling off (monotonic, or a decrease in the firing rate as intensity of the stimulus is increased (nonmonotonic). The majority of neurons in most fields, including AI and PAF, show monotonic behavior. This property has been used to differentiate the Ventral Auditory Field (VAF) which has the unique characteristic of mostly nonmonotonic rate level functions (Polley et al, 2007).

Although some fields respond strongly to pure tones, some belt field respond stronger to noise or other complex sounds better than to pure tones (Pandya et al, 2007). Another type of stimuli used to examine functional properties of auditory neurons is modulated stimuli such as tone trains or sinusoidally modulated sounds (Pandya et al, 2007; Gaese and Ostwald, 1995). Therefore, research in belt fields and nonprimary fields now needs to focus on sounds with more structure than simple unmodulated tones.

There are relatively few studies that explore the functional organization of nonprimary auditory cortical fields in both humans and in animal models. VAF is of particular interest due to its distinguishing characteristics. As mentioned above, VAF is unique in the high percentage of sites that exhibit nonmonotic growth behavior when compared to AI (Doron et al, 2002, Polley et al, 2007). While nonmonotonic growth behavior and basic spectral tuning properties in VAF have been characterized in only one cortical mapping study (Polley et al, 2007), it is unclear how this field responds to temporally modulated sounds. This is because the study by Polley and colleagues (2007) used unmodulated tones and noise to characterize this field. Temporal modulations are important for auditory information processing and different cortical fields are known to have different maximum following rates (Kilgard and Merzenich, 1999). Therefore, experiments in VAF which use complex modulated sounds are required to deter if this cortical sector processes auditory information on a different temporal scale than AI.

Next Summer, a series of experiments will focus on analyzing the tuning properties in VAF to confirm that this field is functionally distinct from AI. We will further characterize VAF by playing trains of tones and noise presented at different rates. In addition, because the rate can be used to study aspects of speech processing (Pandya et al, in review; Toro & Trobalon, 2005) other complex sounds (including speech and non-human primate vocalizations) will be presented as well. The overall objective is to determine if there are other differences between the processing of complex stimuli in AI and VAF.

Following her current work in reviewing the literature, Kathleen has now developed some key hypotheses regarding processing in VAF. For example, the average maximum following rate of neurons in VAF will likely be slower than AI because VAF is found to have longer latencies than AI (Doron et al, 2002; Polley et al, 2007). This finding would be consistent with similar studies in PAF which also shows longer latencies than AI and has been found to have slower maximum rates (Pandya et al, 2007). Next summer, Kathleen will design experiments to test these hypotheses and learn the fundamentals of experimental design. Building upon knowledge gained in previous hearing science coursework, Kathleen will learn about designing complex sounds (such as temporally modulated trains and speech stimuli) for neurophysiologic studies using programs like CoolEdit and SigGen. Kathleen will analyze data using computer programs such as MATLAB and BrainWare. Through analysis of the data, the accuracy of her hypotheses will be tested. Given the multitude of results that these experiments could produce, Kathleen will learn how to interpret a variety of outcomes. For example, a negative result could provide knowledge about the similarities between AI and VAF in processing temporally modulated and speech stimuli. The culmination of her summer research experience may lead to a publication or presentation at a scientific meeting. On a larger scale, Kathleen will contribute to both the hearing science and clinical audiology community by generating new knowledge about auditory cortical processing.

Acknowledgement: I would like to first acknowledge my professor and mentor, Dr. Pritesh Pandya. His incredible support and time has given me the confidence and desire to become a researcher. I would also like to thank Kathi Ritten, Dr. Adrienne Perlman and Dr. Chambers.

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