Browsing by Subject "Echolocation (Physiology)"
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Item The functional role of the dorsal nucleus of the lateral lemniscus in acoustic processing(2000-12) Burger, Robert Michael, 1971-; Pollak, G. D. (George D.), 1942-The mammalian auditory system is composed of a number of parallel and serial pathways devoted to processing different aspects of acoustic signals. The focus of this dissertation is to examine the interactions among nuclei in the pathway devoted to processing interaural intensity disparities (IIDs), the cue animals use to localize high frequency sounds. IIDs are processed by neurons that are excited by sound in one ear and inhibited by sound in the other and thus are referred to as EI neurons. EI response properties are the dominant response feature expressed in three interconnected nuclei that process IIDs; the lateral superior olive (LSO), the dorsal nucleus of the lateral lemniscus (DNLL), and the inferior colliculus (IC). While EI properties are first formed in the LSO, recent studies have shown that EI properties are either modified or created de novo in the ICc through a convergence of inputs from lower nuclei. A prominent GABAergic input from the DNLL provides roughly 30% of the inhibitory innervation to the IC and has been shown to influence IID processing. While this degree of convergence indicates a significant amount of processing, the EI properties expressed in the ICc are strikingly similar to those observed in the LSO. Thus, the central question of these studies is: What is the functional significance of the convergence at the IC if response properties are so similar to those observed below? A possible answer to this question was proposed by Yang and Pollak, following the discovery of a response feature of the DNLL referred to as persistent inhibition. Persistent inhibition is a long lasting inhibition evoked by signals that favor the inhibitory ear. Their hypothesis predicts that ICc neurons that derive their EI properties from DNLL input will differentially process IIDs for multiple signals emanating from different regions of space. Here I confirm this hypotheses with recordings from the auditory system of Mexican-free tailed bats, where I blocked GABAergic inhibition at the IC as well as reversibly inactivated the DNLL while recording from IC neurons. I show that reception of an initial signal reconfigures the IID circuitry by functionally inactivating the DNLL, thereby depriving a population of IC cells of their inhibitory input, and temporarily transforming their EI properties. This property of the DNLL may provide one of the neural mechanisms that underlie the precedence effect.Item Responses of cells of the dorsal nucleus of the lateral lemniscus to species-specific and other complex sounds(2001-12) Bauer, Eric Edmond; Pollak, G. D. (George D.), 1942-The sounds animals hear, whether generated by conspecifics, other species, or the environment, typically contain multiple simultaneous frequencies that change over time. However, most studies of the central auditory system have focused on measuring responses to very simple stimuli, namely individual pure tones. This study investigates how one brainstem auditory nucleus, the dorsal nucleus of the lateral lemniscus (DNLL), responds to complex natural and artificial sounds, and whether the responses to complex sounds can be predicted based on a linear model. Single neurons were recorded in awake Mexican free-tailed bats (Tadarida brasiliensis) during acoustic stimulation. Basic response properties, such as threshold, latency, binaurality, temporal response pattern, and frequency tuning were measured with simple stimuli (tone bursts). The responses to complex sounds, including species-specific communication calls, echolocation pulses, other animal calls, and sounds from a human environment were then obtained from the same cells. Data analysis was divided into two sections. First, responses of DNLL cells to complex sounds were measured and quantified in various ways to develop a better understanding of how this nucleus is activated by these more realistic sound stimuli. Second, predictions of how the cells should have responded to the complex sounds were compared to the actual responses to the sounds. The predictions were generated from two models. The first model was based on the cell’s frequency tuning as measured with simple pure tones. The second model, generated by a more complicated reverse correlation technique, was also used to predict responses to complex sounds. Both of these models were fundamentally linear in nature, and thus allowed an estimation of how linearly DNLL cells integrate synaptic inputs. Using these techniques, it was shown that DNLL cells process complex sounds in a simple linear way. Each cell’s responses are primarily determined by its simple frequency tuning. This applies not only to which sounds a cell will respond to, but also when during those sounds the cell will respond. As a population, then, the activity of cells of the DNLL represent the temporal structure of the spectral content of any sound just as that produced by the Fourier transform and visualized in a spectrogram display.